diff --git a/docs/articles/getting-started.html b/docs/articles/getting-started.html index 9607f6e3..55022b80 100644 --- a/docs/articles/getting-started.html +++ b/docs/articles/getting-started.html @@ -97,18 +97,18 @@

Example tidy_normal() #> # A tibble: 50 × 7 -#> sim_number x y dx dy p q -#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 1.60 -3.66 0.000227 0.5 1.58 -#> 2 1 2 0.985 -3.52 0.000602 0.508 0.841 -#> 3 1 3 0.644 -3.39 0.00142 0.516 0.586 -#> 4 1 4 1.20 -3.25 0.00298 0.524 1.03 -#> 5 1 5 -0.0886 -3.11 0.00555 0.533 0.129 -#> 6 1 6 -0.0347 -2.98 0.00926 0.541 0.161 -#> 7 1 7 1.28 -2.84 0.0139 0.549 1.11 -#> 8 1 8 1.14 -2.70 0.0191 0.557 0.980 -#> 9 1 9 0.0559 -2.57 0.0246 0.565 0.214 -#> 10 1 10 -2.47 -2.43 0.0309 0.573 -Inf +#> sim_number x y dx dy p q +#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 1 1 0.812 -3.35 0.000228 0.5 0.343 +#> 2 1 2 -0.950 -3.21 0.000641 0.508 -0.647 +#> 3 1 3 -1.31 -3.06 0.00158 0.516 -0.903 +#> 4 1 4 -0.306 -2.92 0.00343 0.524 -0.264 +#> 5 1 5 1.16 -2.77 0.00661 0.533 0.551 +#> 6 1 6 -0.314 -2.63 0.0114 0.541 -0.268 +#> 7 1 7 -0.951 -2.48 0.0179 0.549 -0.647 +#> 8 1 8 -0.795 -2.34 0.0261 0.557 -0.547 +#> 9 1 9 2.53 -2.20 0.0367 0.565 Inf +#> 10 1 10 -1.10 -2.05 0.0509 0.573 -0.746 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows

An example plot of the tidy_normal data.

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Examples#> # A tibble: 50,000 × 2 #> sim_number y #> <fct> <dbl> -#> 1 1 13.3 -#> 2 1 19.2 -#> 3 1 19.2 -#> 4 1 27.3 -#> 5 1 10.4 -#> 6 1 21 -#> 7 1 15.5 -#> 8 1 18.7 -#> 9 1 15.2 -#> 10 1 22.8 +#> 1 1 22.8 +#> 2 1 10.4 +#> 3 1 24.4 +#> 4 1 15.8 +#> 5 1 30.4 +#> 6 1 15 +#> 7 1 15.2 +#> 8 1 13.3 +#> 9 1 21.4 +#> 10 1 10.4 #> # … with 49,990 more rows #> # ℹ Use `print(n = ...)` to see more rows @@ -117,16 +117,16 @@

Examples#> # A tibble: 2,000 × 13 #> sim_num…¹ mean_…² media…³ std_val min_val max_val skewn…⁴ kurto…⁵ range iqr #> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 20.6 19.2 6.27 10.4 32.4 0.332 2.29 22 10.5 -#> 2 2 18.1 17.8 5.74 10.4 32.4 0.773 3.39 22 5.8 -#> 3 3 20.1 21 4.54 10.4 30.4 0.0588 3.07 20 3.7 -#> 4 4 19.9 19.2 5.04 10.4 30.4 0.526 2.73 20 6.4 -#> 5 5 20.1 18.7 6.20 10.4 30.4 0.317 1.80 20 11 -#> 6 6 18.7 17.8 5.13 10.4 32.4 1.00 3.90 22 5.8 -#> 7 7 21.6 19.7 8.09 10.4 33.9 0.534 1.74 23.5 15.7 -#> 8 8 17.7 16.4 5.03 10.4 30.4 0.768 3.34 20 4.5 -#> 9 9 18.2 19.2 4.45 10.4 27.3 -0.0667 2.62 16.9 5.8 -#> 10 10 19.5 18.1 5.95 10.4 32.4 0.894 2.82 22 6 +#> 1 1 20.3 21.4 6.52 10.4 30.4 0.112 1.93 20 9.2 +#> 2 2 18.9 19.2 5.00 10.4 30.4 0.316 2.61 20 6.8 +#> 3 3 18.5 17.3 3.98 10.4 27.3 0.406 2.82 16.9 5.8 +#> 4 4 20.4 19.2 4.99 15 33.9 1.12 3.70 18.9 7 +#> 5 5 19.1 17.8 5.72 10.4 32.4 0.899 3.05 22 6.5 +#> 6 6 21.5 21 5.91 14.3 33.9 0.875 2.80 19.6 5 +#> 7 7 19.3 18.1 4.95 10.4 33.9 1.27 5.00 23.5 4.6 +#> 8 8 20.0 16.4 6.71 13.3 33.9 0.838 2.31 20.6 7.8 +#> 9 9 22.5 21 7.06 10.4 33.9 0.0584 2.01 23.5 9.2 +#> 10 10 18.8 15.8 6.09 10.4 33.9 1.58 4.61 23.5 5.5 #> # … with 1,990 more rows, 3 more variables: variance <dbl>, ci_low <dbl>, #> # ci_high <dbl>, and abbreviated variable names ¹​sim_number, ²​mean_val, #> # ³​median_val, ⁴​skewness, ⁵​kurtosis diff --git a/docs/reference/tidy_autoplot-1.png b/docs/reference/tidy_autoplot-1.png index c0821e02..2cb9702a 100644 Binary files a/docs/reference/tidy_autoplot-1.png and b/docs/reference/tidy_autoplot-1.png differ diff --git a/docs/reference/tidy_autoplot-2.png b/docs/reference/tidy_autoplot-2.png index 6deffef9..6481adde 100644 Binary files a/docs/reference/tidy_autoplot-2.png and b/docs/reference/tidy_autoplot-2.png differ diff --git a/docs/reference/tidy_beta.html b/docs/reference/tidy_beta.html index 04d55a52..76337ee6 100644 --- a/docs/reference/tidy_beta.html +++ b/docs/reference/tidy_beta.html @@ -182,18 +182,18 @@

Author<

Examples

tidy_beta()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y       dx      dy      p      q
-#>    <fct>      <int>  <dbl>    <dbl>   <dbl>  <dbl>  <dbl>
-#>  1 1              1 0.612  -0.321   0.00317 0      0.591 
-#>  2 1              2 0.0917 -0.286   0.00743 0.0204 0.0363
-#>  3 1              3 0.943  -0.252   0.0163  0.0408 0.945 
-#>  4 1              4 0.126  -0.217   0.0331  0.0612 0.0733
-#>  5 1              5 0.197  -0.182   0.0631  0.0816 0.149 
-#>  6 1              6 0.101  -0.148   0.112   0.102  0.0463
-#>  7 1              7 0.261  -0.113   0.186   0.122  0.217 
-#>  8 1              8 0.952  -0.0788  0.289   0.143  0.955 
-#>  9 1              9 0.699  -0.0442  0.420   0.163  0.684 
-#> 10 1             10 0.575  -0.00961 0.574   0.184  0.552 
+#>    sim_number     x     y      dx      dy      p     q
+#>    <fct>      <int> <dbl>   <dbl>   <dbl>  <dbl> <dbl>
+#>  1 1              1 0.418 -0.348  0.00182 0      0.417
+#>  2 1              2 0.220 -0.313  0.00445 0.0204 0.218
+#>  3 1              3 0.559 -0.279  0.00997 0.0408 0.558
+#>  4 1              4 0.106 -0.244  0.0206  0.0612 0.103
+#>  5 1              5 0.457 -0.209  0.0393  0.0816 0.456
+#>  6 1              6 0.883 -0.175  0.0692  0.102  0.884
+#>  7 1              7 0.723 -0.140  0.113   0.122  0.724
+#>  8 1              8 0.733 -0.105  0.171   0.143  0.733
+#>  9 1              9 0.799 -0.0708 0.240   0.163  0.799
+#> 10 1             10 0.889 -0.0362 0.317   0.184  0.890
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_burr.html b/docs/reference/tidy_burr.html index 073e926b..22cb9a38 100644 --- a/docs/reference/tidy_burr.html +++ b/docs/reference/tidy_burr.html @@ -190,18 +190,18 @@

Author<

Examples

tidy_burr()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y     dx       dy      p        q
-#>    <fct>      <int>  <dbl>  <dbl>    <dbl>  <dbl>    <dbl>
-#>  1 1              1 1.50   -1.48  0.00166  0      0.0202  
-#>  2 1              2 0.316   0.129 0.389    0.0200 0.00415 
-#>  3 1              3 1.93    1.74  0.158    0.0392 0.0261  
-#>  4 1              4 0.590   3.35  0.0293   0.0577 0.00781 
-#>  5 1              5 0.0130  4.95  0.0140   0.0755 0.000133
-#>  6 1              6 0.265   6.56  0.0220   0.0926 0.00347 
-#>  7 1              7 1.55    8.17  0.000112 0.109  0.0208  
-#>  8 1              8 0.0489  9.78  0.00161  0.125  0.000607
-#>  9 1              9 1.09   11.4   0.0225   0.140  0.0146  
-#> 10 1             10 0.431  13.0   0.000564 0.155  0.00568 
+#>    sim_number     x       y     dx      dy      p       q
+#>    <fct>      <int>   <dbl>  <dbl>   <dbl>  <dbl>   <dbl>
+#>  1 1              1 0.515   -2.55  0.00118 0      0.0152 
+#>  2 1              2 3.61    -1.76  0.0143  0.0200 0.119  
+#>  3 1              3 9.87    -0.960 0.0768  0.0392 0.410  
+#>  4 1              4 0.771   -0.163 0.192   0.0577 0.0231 
+#>  5 1              5 0.329    0.633 0.245   0.0755 0.00962
+#>  6 1              6 0.00644  1.43  0.196   0.0926 0      
+#>  7 1              7 2.39     2.23  0.139   0.109  0.0755 
+#>  8 1              8 4.19     3.02  0.105   0.125  0.141  
+#>  9 1              9 0.0584   3.82  0.0708  0.140  0.00153
+#> 10 1             10 0.728    4.61  0.0319  0.155  0.0218 
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_cauchy.html b/docs/reference/tidy_cauchy.html index 5ac5b8bb..ca22c4a2 100644 --- a/docs/reference/tidy_cauchy.html +++ b/docs/reference/tidy_cauchy.html @@ -176,18 +176,18 @@

Author<

Examples

tidy_cauchy()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y    dx       dy     p     q
-#>    <fct>      <int>  <dbl> <dbl>    <dbl> <dbl> <dbl>
-#>  1 1              1  0.464 -216. 2.15e- 4 0.5   11.4 
-#>  2 1              2 -0.154 -211. 1.11e- 4 0.506 10.3 
-#>  3 1              3  0.107 -207. 0        0.513 10.8 
-#>  4 1              4  1.55  -202. 4.31e-18 0.519 13.9 
-#>  5 1              5 -2.28  -197. 1.55e-18 0.526  7.85
-#>  6 1              6 -0.376 -193. 1.53e-19 0.532 10.0 
-#>  7 1              7  1.97  -188. 0        0.539 15.1 
-#>  8 1              8 -2.02  -184. 2.12e-18 0.545  8.09
-#>  9 1              9  0.111 -179. 1.82e-18 0.552 10.8 
-#> 10 1             10 -3.03  -174. 4.87e-18 0.558  7.23
+#>    sim_number     x        y    dx       dy     p       q
+#>    <fct>      <int>    <dbl> <dbl>    <dbl> <dbl>   <dbl>
+#>  1 1              1 -245.    -246. 6.25e- 4 0.5   -Inf   
+#>  2 1              2   -1.85  -241. 1.93e-13 0.506    3.48
+#>  3 1              3   -6.74  -235. 4.13e-19 0.513    2.85
+#>  4 1              4   -1.23  -230. 0        0.519    3.58
+#>  5 1              5   -0.856 -224. 1.90e-19 0.526    3.64
+#>  6 1              6    0.364 -219. 2.58e-19 0.532    3.86
+#>  7 1              7    4.09  -213. 1.72e-20 0.539    4.70
+#>  8 1              8    0.109 -208. 3.83e-18 0.545    3.81
+#>  9 1              9   -0.289 -202. 3.38e-19 0.552    3.74
+#> 10 1             10    5.12  -197. 0        0.558    5.00
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_chisquare.html b/docs/reference/tidy_chisquare.html index 686a30c9..1306f343 100644 --- a/docs/reference/tidy_chisquare.html +++ b/docs/reference/tidy_chisquare.html @@ -175,18 +175,18 @@

Author<

Examples

tidy_chisquare()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y       dx       dy      p         q
-#>    <fct>      <int>  <dbl>    <dbl>    <dbl>  <dbl>     <dbl>
-#>  1 1              1 1.00   -2.54    0.000994 0      0.0554   
-#>  2 1              2 1.32   -2.26    0.00267  0.0691 0.0958   
-#>  3 1              3 0.587  -1.98    0.00645  0.0978 0.0190   
-#>  4 1              4 1.53   -1.69    0.0140   0.120  0.129    
-#>  5 1              5 0.425  -1.41    0.0275   0.138  0.00997  
-#>  6 1              6 0.0229 -1.13    0.0488   0.155  0.0000288
-#>  7 1              7 1.39   -0.843   0.0785   0.169  0.106    
-#>  8 1              8 2.44   -0.559   0.115    0.183  0.328    
-#>  9 1              9 0.685  -0.276   0.154    0.195  0.0259   
-#> 10 1             10 1.90    0.00723 0.191    0.207  0.199    
+#>    sim_number     x       y      dx      dy      p            q
+#>    <fct>      <int>   <dbl>   <dbl>   <dbl>  <dbl>        <dbl>
+#>  1 1              1  0.0533 -3.27   0.00104 0        0.0000986 
+#>  2 1              2  0.505  -2.91   0.00278 0.0691   0.00887   
+#>  3 1              3  0.0252 -2.55   0.00668 0.0978   0.0000220 
+#>  4 1              4  9.09   -2.19   0.0145  0.120    3.69      
+#>  5 1              5  0.817  -1.83   0.0283  0.138    0.0232    
+#>  6 1              6  0.178  -1.47   0.0499  0.155    0.00110   
+#>  7 1              7  0.0126 -1.11   0.0797  0.169    0.00000550
+#>  8 1              8  5.78   -0.751  0.116   0.183    1.21      
+#>  9 1              9 11.1    -0.391  0.152   0.195  Inf         
+#> 10 1             10  3.14   -0.0315 0.183   0.207    0.343     
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_combine_distributions.html b/docs/reference/tidy_combine_distributions.html index e0887b03..8ddecc4d 100644 --- a/docs/reference/tidy_combine_distributions.html +++ b/docs/reference/tidy_combine_distributions.html @@ -113,18 +113,18 @@

Examples tidy_combine_distributions(tn, tb, tc) #> # A tibble: 150 × 8 -#> sim_number x y dx dy p q dist_type -#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> -#> 1 1 1 -0.856 -2.84 0.000309 0.5 -0.648 Gaussian c(0, 1) -#> 2 1 2 -1.78 -2.73 0.000815 0.508 -Inf Gaussian c(0, 1) -#> 3 1 3 -0.501 -2.61 0.00195 0.516 -0.364 Gaussian c(0, 1) -#> 4 1 4 -0.348 -2.49 0.00423 0.524 -0.251 Gaussian c(0, 1) -#> 5 1 5 0.616 -2.38 0.00836 0.533 0.443 Gaussian c(0, 1) -#> 6 1 6 0.308 -2.26 0.0151 0.541 0.215 Gaussian c(0, 1) -#> 7 1 7 0.576 -2.15 0.0248 0.549 0.413 Gaussian c(0, 1) -#> 8 1 8 -0.115 -2.03 0.0377 0.557 -0.0849 Gaussian c(0, 1) -#> 9 1 9 -0.489 -1.91 0.0531 0.565 -0.355 Gaussian c(0, 1) -#> 10 1 10 -0.377 -1.80 0.0703 0.573 -0.272 Gaussian c(0, 1) +#> sim_number x y dx dy p q dist_type +#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> +#> 1 1 1 0.0440 -3.56 0.000287 0.5 0.139 Gaussian c(0, 1) +#> 2 1 2 -1.06 -3.42 0.000771 0.508 -0.529 Gaussian c(0, 1) +#> 3 1 3 0.643 -3.29 0.00186 0.516 0.509 Gaussian c(0, 1) +#> 4 1 4 -0.319 -3.15 0.00404 0.524 -0.0734 Gaussian c(0, 1) +#> 5 1 5 -0.174 -3.01 0.00789 0.533 0.0115 Gaussian c(0, 1) +#> 6 1 6 0.399 -2.87 0.0140 0.541 0.353 Gaussian c(0, 1) +#> 7 1 7 0.659 -2.74 0.0225 0.549 0.520 Gaussian c(0, 1) +#> 8 1 8 0.373 -2.60 0.0335 0.557 0.337 Gaussian c(0, 1) +#> 9 1 9 -2.34 -2.46 0.0465 0.565 -Inf Gaussian c(0, 1) +#> 10 1 10 -1.52 -2.32 0.0615 0.573 -0.871 Gaussian c(0, 1) #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows @@ -139,16 +139,16 @@

Examples#> # A tibble: 200 × 8 #> sim_number x y dx dy p q dist_type #> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> -#> 1 1 1 -0.731 -3.67 0.000250 0.5 -0.308 Gaussian c(0, 1) -#> 2 1 2 -0.475 -3.53 0.000752 0.508 -0.171 Gaussian c(0, 1) -#> 3 1 3 -1.85 -3.38 0.00196 0.516 -1.05 Gaussian c(0, 1) -#> 4 1 4 -0.0244 -3.24 0.00445 0.524 0.0628 Gaussian c(0, 1) -#> 5 1 5 -1.48 -3.10 0.00879 0.533 -0.759 Gaussian c(0, 1) -#> 6 1 6 0.708 -2.95 0.0153 0.541 0.458 Gaussian c(0, 1) -#> 7 1 7 1.96 -2.81 0.0238 0.549 1.51 Gaussian c(0, 1) -#> 8 1 8 1.03 -2.66 0.0334 0.557 0.651 Gaussian c(0, 1) -#> 9 1 9 0.219 -2.52 0.0434 0.565 0.190 Gaussian c(0, 1) -#> 10 1 10 0.203 -2.38 0.0535 0.573 0.182 Gaussian c(0, 1) +#> 1 1 1 0.153 -3.28 0.000244 0.5 0.182 Gaussian c(0, 1) +#> 2 1 2 -0.897 -3.15 0.000637 0.508 -0.504 Gaussian c(0, 1) +#> 3 1 3 0.461 -3.03 0.00151 0.516 0.385 Gaussian c(0, 1) +#> 4 1 4 0.0108 -2.90 0.00327 0.524 0.0912 Gaussian c(0, 1) +#> 5 1 5 0.0208 -2.77 0.00650 0.533 0.0975 Gaussian c(0, 1) +#> 6 1 6 -1.36 -2.64 0.0120 0.541 -0.876 Gaussian c(0, 1) +#> 7 1 7 0.360 -2.51 0.0206 0.549 0.317 Gaussian c(0, 1) +#> 8 1 8 -1.67 -2.38 0.0336 0.557 -1.22 Gaussian c(0, 1) +#> 9 1 9 0.554 -2.25 0.0520 0.565 0.450 Gaussian c(0, 1) +#> 10 1 10 -1.40 -2.13 0.0768 0.573 -0.918 Gaussian c(0, 1) #> # … with 190 more rows #> # ℹ Use `print(n = ...)` to see more rows diff --git a/docs/reference/tidy_combined_autoplot-1.png b/docs/reference/tidy_combined_autoplot-1.png index 7cdc4e3c..6090b7c2 100644 Binary files a/docs/reference/tidy_combined_autoplot-1.png and b/docs/reference/tidy_combined_autoplot-1.png differ diff --git a/docs/reference/tidy_combined_autoplot-2.png b/docs/reference/tidy_combined_autoplot-2.png index d3631a4a..97d59325 100644 Binary files a/docs/reference/tidy_combined_autoplot-2.png and b/docs/reference/tidy_combined_autoplot-2.png differ diff --git a/docs/reference/tidy_combined_autoplot.html b/docs/reference/tidy_combined_autoplot.html index a4f1b025..84d56aaa 100644 --- a/docs/reference/tidy_combined_autoplot.html +++ b/docs/reference/tidy_combined_autoplot.html @@ -181,18 +181,18 @@

Examples combined_tbl #> # A tibble: 150 × 8 -#> sim_number x y dx dy p q dist_type -#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> -#> 1 1 1 1.19 -3.78 0.000213 0.5 0.925 Gaussian c(0, 1) -#> 2 1 2 1.99 -3.64 0.000558 0.508 Inf Gaussian c(0, 1) -#> 3 1 3 0.433 -3.49 0.00131 0.516 0.396 Gaussian c(0, 1) -#> 4 1 4 1.24 -3.35 0.00274 0.524 0.966 Gaussian c(0, 1) -#> 5 1 5 -0.192 -3.21 0.00516 0.533 0.0378 Gaussian c(0, 1) -#> 6 1 6 -0.369 -3.06 0.00878 0.541 -0.0606 Gaussian c(0, 1) -#> 7 1 7 0.305 -2.92 0.0136 0.549 0.320 Gaussian c(0, 1) -#> 8 1 8 -0.632 -2.78 0.0195 0.557 -0.209 Gaussian c(0, 1) -#> 9 1 9 -1.91 -2.63 0.0263 0.565 -1.11 Gaussian c(0, 1) -#> 10 1 10 -0.379 -2.49 0.0342 0.573 -0.0663 Gaussian c(0, 1) +#> sim_number x y dx dy p q dist_type +#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> +#> 1 1 1 -0.386 -4.69 0.000177 0.5 -0.0743 Gaussian c(0, 1) +#> 2 1 2 -1.74 -4.51 0.000490 0.508 -0.698 Gaussian c(0, 1) +#> 3 1 3 -0.475 -4.33 0.00119 0.516 -0.112 Gaussian c(0, 1) +#> 4 1 4 -1.55 -4.14 0.00253 0.524 -0.603 Gaussian c(0, 1) +#> 5 1 5 -1.39 -3.96 0.00473 0.533 -0.521 Gaussian c(0, 1) +#> 6 1 6 0.989 -3.78 0.00778 0.541 0.531 Gaussian c(0, 1) +#> 7 1 7 -0.0218 -3.60 0.0113 0.549 0.0800 Gaussian c(0, 1) +#> 8 1 8 -1.71 -3.41 0.0145 0.557 -0.684 Gaussian c(0, 1) +#> 9 1 9 -1.23 -3.23 0.0167 0.565 -0.445 Gaussian c(0, 1) +#> 10 1 10 0.611 -3.05 0.0183 0.573 0.355 Gaussian c(0, 1) #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows diff --git a/docs/reference/tidy_distribution_comparison.html b/docs/reference/tidy_distribution_comparison.html index 94820ba3..0adbc9bd 100644 --- a/docs/reference/tidy_distribution_comparison.html +++ b/docs/reference/tidy_distribution_comparison.html @@ -118,25 +118,25 @@

Examples#> # A tibble: 9 × 2 #> dist_with_params abs_tot_deviance #> <chr> <dbl> -#> 1 Lognormal c(2.96, 0.29) 1.57 -#> 2 Gamma c(11.47, 1.75) 1.92 -#> 3 Beta c(1.11, 1.58, 0) 2.27 -#> 4 Weibull c(3.58, 22.29) 2.79 -#> 5 Pareto c(10.4, 1.62) 2.83 -#> 6 Uniform c(8.34, 31.84) 3.77 -#> 7 Logistic c(20.09, 3.27) 4.47 -#> 8 Exponential c(0.05) 6.55 -#> 9 Cauchy c(19.2, 7.38) 10.6 +#> 1 Beta c(1.11, 1.58, 0) 0.0880 +#> 2 Uniform c(8.34, 31.84) 1.18 +#> 3 Weibull c(3.58, 22.29) 1.43 +#> 4 Cauchy c(19.2, 7.38) 1.79 +#> 5 Lognormal c(2.96, 0.29) 2.76 +#> 6 Exponential c(0.05) 3.09 +#> 7 Gamma c(11.47, 1.75) 3.20 +#> 8 Logistic c(20.09, 3.27) 6.47 +#> 9 Pareto c(10.4, 1.62) 6.64 xd <- trunc(xc) tidy_distribution_comparison(xd, "discrete") #> # A tibble: 4 × 2 #> dist_with_params abs_tot_deviance #> <chr> <dbl> -#> 1 Hypergeometric c(21, 11, 21) 0.188 -#> 2 Poisson c(19.69) 0.288 -#> 3 Binomial c(32, 0.03) 3.81 -#> 4 Geometric c(0.05) 5.82 +#> 1 Hypergeometric c(21, 11, 21) 0.978 +#> 2 Geometric c(0.05) 1.72 +#> 3 Binomial c(32, 0.03) 2.81 +#> 4 Poisson c(19.69) 6.86 diff --git a/docs/reference/tidy_distribution_summary_tbl.html b/docs/reference/tidy_distribution_summary_tbl.html index 828f7190..2620142f 100644 --- a/docs/reference/tidy_distribution_summary_tbl.html +++ b/docs/reference/tidy_distribution_summary_tbl.html @@ -124,21 +124,21 @@

Examples#> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 -0.00689 -0.0508 0.985 -2.62 2.48 -0.0740 2.66 5.09 1.42 0.970 +#> 1 -0.0300 -0.0569 0.939 -2.77 2.54 0.0167 2.65 5.32 1.36 0.881 #> # … with 2 more variables: ci_low <dbl>, ci_high <dbl>, and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance #> # ℹ Use `colnames()` to see all variable names tidy_distribution_summary_tbl(tn, sim_number) #> # A tibble: 5 × 13 -#> sim_num…¹ mean_val media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr +#> sim_number mean_…¹ media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 -0.00930 0.0472 1.14 -2.62 2.23 -0.198 2.33 4.84 1.73 -#> 2 2 0.0438 -0.0657 0.963 -2.04 2.36 0.196 2.94 4.39 1.22 -#> 3 3 -0.207 -0.236 0.997 -2.59 1.74 -0.153 2.40 4.33 1.43 -#> 4 4 0.273 0.213 0.971 -1.96 2.48 -0.0985 2.59 4.44 1.20 -#> 5 5 -0.135 -0.122 0.793 -1.83 1.38 -0.199 2.34 3.21 1.21 +#> 1 1 -0.0470 -0.210 0.880 -1.46 2.54 0.651 3.16 4.00 1.13 +#> 2 2 0.0211 0.0589 0.876 -2.09 1.85 -0.117 2.39 3.94 1.46 +#> 3 3 -0.0889 -0.117 0.978 -2.77 1.91 -0.168 3.11 4.68 1.34 +#> 4 4 -0.0121 -0.0495 0.945 -1.47 2.00 0.244 1.99 3.47 1.51 +#> 5 5 -0.0231 0.203 1.04 -2.30 1.93 -0.287 2.43 4.23 1.42 #> # … with 3 more variables: variance <dbl>, ci_low <dbl>, ci_high <dbl>, and -#> # abbreviated variable names ¹​sim_number, ²​median_val, ³​skewness, ⁴​kurtosis +#> # abbreviated variable names ¹​mean_val, ²​median_val, ³​skewness, ⁴​kurtosis #> # ℹ Use `colnames()` to see all variable names data_tbl <- tidy_combine_distributions(tn, tb) @@ -147,18 +147,18 @@

Examples#> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 0.261 0.422 0.771 -2.62 2.48 -0.859 4.30 5.09 0.795 0.595 +#> 1 0.235 0.352 0.742 -2.77 2.54 -0.758 4.05 5.32 0.766 0.551 #> # … with 2 more variables: ci_low <dbl>, ci_high <dbl>, and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance #> # ℹ Use `colnames()` to see all variable names tidy_distribution_summary_tbl(data_tbl, dist_type) #> # A tibble: 2 × 13 -#> dist_t…¹ mean_val media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr +#> dist_type mean_…¹ media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 Gaussia… -0.00689 -0.0508 0.985 -2.62e+0 2.48 -0.0740 2.66 5.09 1.42 -#> 2 Beta c(… 0.529 0.526 0.279 2.34e-4 0.999 -0.0998 1.90 0.999 0.446 +#> 1 Gaussian… -0.0300 -0.0569 0.939 -2.77 2.54 0.0167 2.65 5.32 1.36 +#> 2 Beta c(1… 0.500 0.497 0.286 0.00391 1.00 0.0366 1.83 0.996 0.483 #> # … with 3 more variables: variance <dbl>, ci_low <dbl>, ci_high <dbl>, and -#> # abbreviated variable names ¹​dist_type, ²​median_val, ³​skewness, ⁴​kurtosis +#> # abbreviated variable names ¹​mean_val, ²​median_val, ³​skewness, ⁴​kurtosis #> # ℹ Use `colnames()` to see all variable names diff --git a/docs/reference/tidy_empirical.html b/docs/reference/tidy_empirical.html index 3fcac8d0..e18e642b 100644 --- a/docs/reference/tidy_empirical.html +++ b/docs/reference/tidy_empirical.html @@ -120,18 +120,18 @@

Examples#> # ℹ Use `print(n = ...)` to see more rows tidy_empirical(.x = x, .num_sims = 10, .distribution_type = "continuous") #> # A tibble: 320 × 7 -#> sim_number x y dx dy p q -#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 21.5 3.20 0.0000602 0.719 10.4 -#> 2 1 2 19.7 4.42 0.000250 0.562 13.3 -#> 3 1 3 14.3 5.64 0.000821 0.125 13.3 -#> 4 1 4 19.7 6.87 0.00218 0.562 14.3 -#> 5 1 5 33.9 8.09 0.00487 1 14.3 -#> 6 1 6 22.8 9.31 0.00954 0.781 15.2 -#> 7 1 7 24.4 10.5 0.0169 0.812 15.2 -#> 8 1 8 14.3 11.8 0.0274 0.125 15.2 -#> 9 1 9 15.2 13.0 0.0396 0.25 15.8 -#> 10 1 10 18.7 14.2 0.0505 0.469 16.4 +#> sim_number x y dx dy p q +#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 1 1 10.4 3.80 0.000128 0.0625 10.4 +#> 2 1 2 21.4 4.98 0.000554 0.688 10.4 +#> 3 1 3 19.2 6.17 0.00182 0.531 14.3 +#> 4 1 4 15.2 7.35 0.00453 0.25 14.3 +#> 5 1 5 32.4 8.54 0.00889 0.969 14.7 +#> 6 1 6 30.4 9.72 0.0147 0.938 14.7 +#> 7 1 7 14.7 10.9 0.0229 0.156 15.2 +#> 8 1 8 22.8 12.1 0.0362 0.781 15.2 +#> 9 1 9 21.4 13.3 0.0551 0.688 15.2 +#> 10 1 10 16.4 14.5 0.0737 0.344 15.2 #> # … with 310 more rows #> # ℹ Use `print(n = ...)` to see more rows diff --git a/docs/reference/tidy_exponential.html b/docs/reference/tidy_exponential.html index c3461ab7..df7f8ed5 100644 --- a/docs/reference/tidy_exponential.html +++ b/docs/reference/tidy_exponential.html @@ -173,18 +173,18 @@

Author<

Examples

tidy_exponential()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y      dx      dy      p       q
-#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>   <dbl>
-#>  1 1              1 0.953  -0.603  0.00253 0      0.304  
-#>  2 1              2 0.956  -0.505  0.0101  0.0202 0.305  
-#>  3 1              3 1.02   -0.406  0.0322  0.0400 0.329  
-#>  4 1              4 0.233  -0.308  0.0833  0.0594 0.0636 
-#>  5 1              5 0.635  -0.210  0.176   0.0784 0.191  
-#>  6 1              6 0.938  -0.111  0.307   0.0970 0.299  
-#>  7 1              7 0.0366 -0.0131 0.455   0.115  0.00691
-#>  8 1              8 0.506   0.0852 0.588   0.133  0.148  
-#>  9 1              9 0.333   0.183  0.683   0.151  0.0937 
-#> 10 1             10 2.16    0.282  0.733   0.168  0.915  
+#>    sim_number     x      y       dx      dy      p       q
+#>    <fct>      <int>  <dbl>    <dbl>   <dbl>  <dbl>   <dbl>
+#>  1 1              1 0.465  -1.14    0.00160 0      0.0858 
+#>  2 1              2 0.545  -0.979   0.00578 0.0202 0.101  
+#>  3 1              3 0.468  -0.817   0.0175  0.0400 0.0864 
+#>  4 1              4 0.0529 -0.655   0.0453  0.0594 0.00917
+#>  5 1              5 0.326  -0.494   0.0993  0.0784 0.0594 
+#>  6 1              6 3.90   -0.332   0.186   0.0970 1.18   
+#>  7 1              7 0.0343 -0.170   0.299   0.115  0.00584
+#>  8 1              8 1.11   -0.00882 0.417   0.133  0.218  
+#>  9 1              9 2.11    0.153   0.507   0.151  0.467  
+#> 10 1             10 1.61    0.314   0.543   0.168  0.336  
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_f.html b/docs/reference/tidy_f.html index 90e01776..21e6ac1c 100644 --- a/docs/reference/tidy_f.html +++ b/docs/reference/tidy_f.html @@ -179,18 +179,18 @@

Author<

Examples

tidy_f()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y     dx       dy      p        q
-#>    <fct>      <int>   <dbl>  <dbl>    <dbl>  <dbl>    <dbl>
-#>  1 1              1  0.374   -4.63 1.92e- 2 0      8.35e- 8
-#>  2 1              2  1.65    37.0  3.46e- 6 0.0903 1.62e- 6
-#>  3 1              3  0.708   78.6  2.11e- 4 0.127  3.00e- 7
-#>  4 1              4 26.2    120.   9.71e-20 0.154  4.09e- 4
-#>  5 1              5  0.0273 162.   4.06e-23 0.177  4.41e-10
-#>  6 1              6 14.5    204.   0        0.197  1.25e- 4
-#>  7 1              7  1.05   245.   1.46e-19 0.214  6.57e- 7
-#>  8 1              8  0.103  287.   0        0.230  6.38e- 9
-#>  9 1              9  0.623  328.   4.04e-19 0.244  2.32e- 7
-#> 10 1             10  0.145  370.   3.99e-20 0.258  1.26e- 8
+#>    sim_number     x           y    dx       dy      p        q
+#>    <fct>      <int>       <dbl> <dbl>    <dbl>  <dbl>    <dbl>
+#>  1 1              1   0.0000562 -2.28 2.84e- 3 0      0       
+#>  2 1              2   0.460      3.05 6.62e- 2 0.0903 7.94e- 6
+#>  3 1              3   0.163      8.37 9.38e- 3 0.127  1.00e- 6
+#>  4 1              4   3.92      13.7  1.55e- 3 0.154  5.76e- 4
+#>  5 1              5   0.00199   19.0  1.11e- 2 0.177  1.40e-10
+#>  6 1              6   0.0288    24.4  9.22e- 3 0.197  3.10e- 8
+#>  7 1              7   0.0114    29.7  8.77e-11 0.214  4.81e- 9
+#>  8 1              8   0.526     35.0  0        0.230  1.04e- 5
+#>  9 1              9   1.29      40.3  8.03e-19 0.244  6.20e- 5
+#> 10 1             10 103.        45.7  1.51e-18 0.258  5.34e- 1
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_four_autoplot-1.png b/docs/reference/tidy_four_autoplot-1.png index ee1c0e0e..8a01af45 100644 Binary files a/docs/reference/tidy_four_autoplot-1.png and b/docs/reference/tidy_four_autoplot-1.png differ diff --git a/docs/reference/tidy_gamma.html b/docs/reference/tidy_gamma.html index 5e63c406..c65d082a 100644 --- a/docs/reference/tidy_gamma.html +++ b/docs/reference/tidy_gamma.html @@ -179,18 +179,18 @@

Author<

Examples

tidy_gamma()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y      dx      dy      p          q
-#>    <fct>      <int>   <dbl>   <dbl>   <dbl>  <dbl>      <dbl>
-#>  1 1              1 1.18    -0.318  0.00624 0      Inf       
-#>  2 1              2 0.0931  -0.280  0.0177  0.0658   0.0238  
-#>  3 1              3 0.735   -0.243  0.0450  0.127    0.293   
-#>  4 1              4 0.123   -0.206  0.102   0.185    0.0321  
-#>  5 1              5 0.0557  -0.169  0.208   0.238    0.0137  
-#>  6 1              6 0.121   -0.132  0.380   0.288    0.0317  
-#>  7 1              7 0.0621  -0.0953 0.626   0.335    0.0154  
-#>  8 1              8 0.189   -0.0582 0.929   0.379    0.0518  
-#>  9 1              9 0.275   -0.0212 1.25    0.420    0.0790  
-#> 10 1             10 0.00619  0.0159 1.53    0.458    0.000687
+#>    sim_number     x      y      dx      dy      p       q
+#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>   <dbl>
+#>  1 1              1 0.0134 -0.295  0.00458 0      0      
+#>  2 1              2 0.0482 -0.243  0.0204  0.0658 0.00539
+#>  3 1              3 0.160  -0.190  0.0715  0.127  0.0235 
+#>  4 1              4 0.106  -0.138  0.198   0.185  0.0147 
+#>  5 1              5 0.505  -0.0857 0.442   0.238  0.0872 
+#>  6 1              6 0.125  -0.0333 0.800   0.288  0.0177 
+#>  7 1              7 0.601   0.0191 1.20    0.335  0.108  
+#>  8 1              8 0.466   0.0715 1.55    0.379  0.0792 
+#>  9 1              9 0.0363  0.124  1.74    0.420  0.00353
+#> 10 1             10 0.0461  0.176  1.77    0.458  0.00508
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_generalized_beta.html b/docs/reference/tidy_generalized_beta.html index 2ba90107..7a8fa6f8 100644 --- a/docs/reference/tidy_generalized_beta.html +++ b/docs/reference/tidy_generalized_beta.html @@ -201,16 +201,16 @@

Examples#> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 0.840 -0.398 0.00289 0 0.839 -#> 2 1 2 0.383 -0.362 0.00658 0.0204 0.377 -#> 3 1 3 0.584 -0.325 0.0140 0.0408 0.581 -#> 4 1 4 0.964 -0.288 0.0277 0.0612 0.965 -#> 5 1 5 0.0306 -0.251 0.0514 0.0816 0.0211 -#> 6 1 6 0.117 -0.214 0.0894 0.102 0.109 -#> 7 1 7 0.968 -0.177 0.146 0.122 0.968 -#> 8 1 8 0.915 -0.140 0.222 0.143 0.915 -#> 9 1 9 0.646 -0.104 0.319 0.163 0.643 -#> 10 1 10 0.935 -0.0668 0.430 0.184 0.936 +#> 1 1 1 0.300 -0.350 0.00285 0 0.293 +#> 2 1 2 0.638 -0.315 0.00675 0.0204 0.635 +#> 3 1 3 0.603 -0.280 0.0147 0.0408 0.600 +#> 4 1 4 0.656 -0.245 0.0295 0.0612 0.652 +#> 5 1 5 0.688 -0.210 0.0547 0.0816 0.685 +#> 6 1 6 0.895 -0.175 0.0933 0.102 0.895 +#> 7 1 7 0.509 -0.140 0.147 0.122 0.504 +#> 8 1 8 0.0368 -0.106 0.214 0.143 0.0272 +#> 9 1 9 1.00 -0.0706 0.289 0.163 1 +#> 10 1 10 0.599 -0.0358 0.364 0.184 0.595 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows diff --git a/docs/reference/tidy_generalized_pareto.html b/docs/reference/tidy_generalized_pareto.html index 2b7bdb4e..493c59fc 100644 --- a/docs/reference/tidy_generalized_pareto.html +++ b/docs/reference/tidy_generalized_pareto.html @@ -197,18 +197,18 @@

Author<

Examples

tidy_generalized_pareto()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y     dx       dy      p        q
-#>    <fct>      <int>  <dbl>  <dbl>    <dbl>  <dbl>    <dbl>
-#>  1 1              1 0.346  -1.48  1.82e- 3 0      0.00286 
-#>  2 1              2 5.12    0.864 3.71e- 1 0.02   0.0477  
-#>  3 1              3 1.62    3.21  2.86e- 2 0.0392 0.0145  
-#>  4 1              4 0.307   5.56  3.87e- 2 0.0577 0.00251 
-#>  5 1              5 0.0850  7.91  5.49e- 4 0.0755 0.000521
-#>  6 1              6 1.28   10.3   3.75e-10 0.0926 0.0113  
-#>  7 1              7 4.44   12.6   6.56e- 3 0.109  0.0410  
-#>  8 1              8 0.353  15.0   7.15e- 5 0.125  0.00292 
-#>  9 1              9 0.0267 17.3   4.53e-16 0.140  0       
-#> 10 1             10 0.0598 19.6   0        0.155  0.000296
+#>    sim_number     x     y     dx       dy      p       q
+#>    <fct>      <int> <dbl>  <dbl>    <dbl>  <dbl>   <dbl>
+#>  1 1              1 2.31  -2.57  0.000800 0      0.0478 
+#>  2 1              2 1.46  -1.46  0.0240   0.02   0.0294 
+#>  3 1              3 2.68  -0.341 0.160    0.0392 0.0561 
+#>  4 1              4 1.61   0.776 0.266    0.0577 0.0325 
+#>  5 1              5 0.456  1.89  0.152    0.0755 0.00822
+#>  6 1              6 0.158  3.01  0.0821   0.0926 0.00213
+#>  7 1              7 0.884  4.13  0.0468   0.109  0.0171 
+#>  8 1              8 0.691  5.24  0.0258   0.125  0.0131 
+#>  9 1              9 0.333  6.36  0.0264   0.140  0.00569
+#> 10 1             10 3.07   7.48  0.0223   0.155  0.0648 
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_inverse_burr.html b/docs/reference/tidy_inverse_burr.html index b0f80a6c..1f2410e0 100644 --- a/docs/reference/tidy_inverse_burr.html +++ b/docs/reference/tidy_inverse_burr.html @@ -196,18 +196,18 @@

Author<

Examples

tidy_inverse_burr()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y     dx      dy      p       q
-#>    <fct>      <int>  <dbl>  <dbl>   <dbl>  <dbl>   <dbl>
-#>  1 1              1  0.657 -2.14  0.00140 0      0.00901
-#>  2 1              2  0.685 -0.629 0.121   0.02   0.00941
-#>  3 1              3 15.7    0.883 0.276   0.0392 0.289  
-#>  4 1              4  0.132  2.39  0.112   0.0577 0.00140
-#>  5 1              5  0.418  3.91  0.0416  0.0755 0.00553
-#>  6 1              6  6.32   5.42  0.00783 0.0926 0.0992 
-#>  7 1              7  3.70   6.93  0.0184  0.109  0.0555 
-#>  8 1              8  0.222  8.44  0.00272 0.125  0.00270
-#>  9 1              9  1.41   9.95  0.0104  0.140  0.0201 
-#> 10 1             10  0.755 11.5   0.00235 0.155  0.0104 
+#>    sim_number     x      y     dx       dy      p       q
+#>    <fct>      <int>  <dbl>  <dbl>    <dbl>  <dbl>   <dbl>
+#>  1 1              1  0.396 -0.999 4.51e- 3 0      0.00233
+#>  2 1              2  0.439  2.34  4.96e- 2 0.02   0.00260
+#>  3 1              3  1.01   5.68  3.15e- 2 0.0392 0.00615
+#>  4 1              4 22.9    9.03  1.79e- 2 0.0577 0.165  
+#>  5 1              5  0.311 12.4   0        0.0755 0.00180
+#>  6 1              6  0.831 15.7   6.77e-18 0.0926 0.00504
+#>  7 1              7  0.817 19.1   2.00e- 2 0.109  0.00495
+#>  8 1              8 19.1   22.4   9.65e- 3 0.125  0.133  
+#>  9 1              9  1.15  25.7   1.39e-15 0.140  0.00704
+#> 10 1             10  2.13  29.1   0        0.155  0.0132 
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_inverse_exponential.html b/docs/reference/tidy_inverse_exponential.html index 0a6c71ae..b955705b 100644 --- a/docs/reference/tidy_inverse_exponential.html +++ b/docs/reference/tidy_inverse_exponential.html @@ -183,18 +183,18 @@

Author<

Examples

tidy_inverse_exponential()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y     dx       dy        p     q
-#>    <fct>      <int>  <dbl>  <dbl>    <dbl>    <dbl> <dbl>
-#>  1 1              1  1.63  -3.20  0.000689 0        0.242
-#>  2 1              2  0.704 -1.19  0.0487   5.24e-22 0.194
-#>  3 1              3  9.10   0.813 0.197    2.29e-11 0.429
-#>  4 1              4  0.570  2.82  0.105    8.06e- 8 0.184
-#>  5 1              5  0.427  4.83  0.0727   4.79e- 6 0.170
-#>  6 1              6  0.918  6.84  0.0260   5.55e- 5 0.208
-#>  7 1              7  3.84   8.84  0.0149   2.84e- 4 0.311
-#>  8 1              8  1.93  10.9   0.00507  9.12e- 4 0.253
-#>  9 1              9 12.9   12.9   0.00709  2.19e- 3 0.507
-#> 10 1             10  5.72  14.9   0.00166  4.32e- 3 0.357
+#>    sim_number     x     y     dx       dy        p     q
+#>    <fct>      <int> <dbl>  <dbl>    <dbl>    <dbl> <dbl>
+#>  1 1              1 0.640 -1.28  0.000613 0        0.193
+#>  2 1              2 1.02   0.306 0.277    5.24e-22 0.221
+#>  3 1              3 0.333  1.90  0.213    2.29e-11 0.155
+#>  4 1              4 9.10   3.48  0.0163   8.06e- 8 0.469
+#>  5 1              5 4.71   5.07  0.0188   4.79e- 6 0.355
+#>  6 1              6 0.507  6.66  0.0224   5.55e- 5 0.180
+#>  7 1              7 0.759  8.25  0.0221   2.84e- 4 0.203
+#>  8 1              8 0.671  9.84  0.00577  9.12e- 4 0.196
+#>  9 1              9 0.467 11.4   0.0162   2.19e- 3 0.175
+#> 10 1             10 1.42  13.0   0.0130   4.32e- 3 0.242
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
 
diff --git a/docs/reference/tidy_inverse_gamma.html b/docs/reference/tidy_inverse_gamma.html
index 3520660d..d4e5d592 100644
--- a/docs/reference/tidy_inverse_gamma.html
+++ b/docs/reference/tidy_inverse_gamma.html
@@ -195,16 +195,16 @@ 
Examples#> # A tibble: 50 × 7
 #>    sim_number     x     y     dx       dy        p     q
 #>    <fct>      <int> <dbl>  <dbl>    <dbl>    <dbl> <dbl>
-#>  1 1              1 0.392  -1.87 1.10e- 2 0        0.106
-#>  2 1              2 4.84   16.4  1.45e- 4 5.24e-22 0.189
-#>  3 1              3 3.22   34.7  0        2.29e-11 0.175
-#>  4 1              4 0.972  53.0  0        8.06e- 8 0.139
-#>  5 1              5 0.472  71.3  2.38e-15 4.79e- 6 0.115
-#>  6 1              6 8.46   89.5  0        5.55e- 5 0.213
-#>  7 1              7 0.498 108.   9.50e-19 2.84e- 4 0.118
-#>  8 1              8 1.13  126.   0        9.12e- 4 0.143
-#>  9 1              9 1.21  144.   8.60e-19 2.19e- 3 0.145
-#> 10 1             10 0.461 163.   0        4.32e- 3 0.114
+#>  1 1              1 0.500 -1.12  0.000570 0        0.219
+#>  2 1              2 0.650 -0.323 0.0648   5.24e-22 0.236
+#>  3 1              3 2.28   0.473 0.406    2.29e-11 0.354
+#>  4 1              4 3.01   1.27  0.330    8.06e- 8 0.394
+#>  5 1              5 0.494  2.06  0.207    4.79e- 6 0.218
+#>  6 1              6 2.43   2.86  0.0660   5.55e- 5 0.362
+#>  7 1              7 0.682  3.66  0.0153   2.84e- 4 0.240
+#>  8 1              8 4.79   4.45  0.0476   9.12e- 4 0.486
+#>  9 1              9 0.772  5.25  0.0231   2.19e- 3 0.248
+#> 10 1             10 0.802  6.04  0.0197   4.32e- 3 0.251
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_inverse_normal.html b/docs/reference/tidy_inverse_normal.html index 56035dfe..21420834 100644 --- a/docs/reference/tidy_inverse_normal.html +++ b/docs/reference/tidy_inverse_normal.html @@ -191,16 +191,16 @@

Examples#> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 1.32 -0.763 0.00161 0 0.338 -#> 2 1 2 1.58 -0.614 0.00623 6.89e-12 0.385 -#> 3 1 3 1.42 -0.466 0.0199 1.98e- 6 0.356 -#> 4 1 4 0.704 -0.318 0.0529 1.40e- 4 0.228 -#> 5 1 5 0.248 -0.169 0.118 1.22e- 3 0.100 -#> 6 1 6 0.846 -0.0210 0.220 4.54e- 3 0.254 -#> 7 1 7 0.350 0.127 0.349 1.10e- 2 0.147 -#> 8 1 8 0.426 0.276 0.473 2.09e- 2 0.169 -#> 9 1 9 0.755 0.424 0.556 3.39e- 2 0.238 -#> 10 1 10 0.498 0.572 0.580 4.96e- 2 0.186 +#> 1 1 1 0.668 -0.786 0.00129 0 0.223 +#> 2 1 2 0.828 -0.614 0.00743 6.89e-12 0.247 +#> 3 1 3 0.193 -0.442 0.0314 1.98e- 6 0.130 +#> 4 1 4 1.55 -0.270 0.0975 1.40e- 4 0.348 +#> 5 1 5 0.208 -0.0982 0.227 1.22e- 3 0.134 +#> 6 1 6 1.30 0.0738 0.404 4.54e- 3 0.314 +#> 7 1 7 0.301 0.246 0.572 1.10e- 2 0.158 +#> 8 1 8 0.267 0.418 0.672 2.09e- 2 0.150 +#> 9 1 9 0.811 0.590 0.681 3.39e- 2 0.244 +#> 10 1 10 0.887 0.762 0.609 4.96e- 2 0.255 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows diff --git a/docs/reference/tidy_inverse_pareto.html b/docs/reference/tidy_inverse_pareto.html index 88463017..b4401a26 100644 --- a/docs/reference/tidy_inverse_pareto.html +++ b/docs/reference/tidy_inverse_pareto.html @@ -185,18 +185,18 @@

Author<

Examples

tidy_inverse_pareto()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y     dx      dy      p         q
-#>    <fct>      <int>  <dbl>  <dbl>   <dbl>  <dbl>     <dbl>
-#>  1 1              1 4.07   -2.09  0.00140 0      0.0513   
-#>  2 1              2 0.512  -0.310 0.199   0.02   0.00602  
-#>  3 1              3 1.11    1.47  0.194   0.0392 0.0134   
-#>  4 1              4 0.108   3.25  0.0740  0.0577 0.00112  
-#>  5 1              5 0.0590  5.03  0.0227  0.0755 0.000532 
-#>  6 1              6 0.306   6.81  0.00741 0.0926 0.00351  
-#>  7 1              7 0.0178  8.59  0.00764 0.109  0.0000354
-#>  8 1              8 2.19   10.4   0.00306 0.125  0.0269   
-#>  9 1              9 7.97   12.2   0.0186  0.140  0.106    
-#> 10 1             10 2.88   13.9   0.00106 0.155  0.0357   
+#>    sim_number     x        y     dx      dy      p         q
+#>    <fct>      <int>    <dbl>  <dbl>   <dbl>  <dbl>     <dbl>
+#>  1 1              1  0.104   -1.98  0.00148 0        0.00579
+#>  2 1              2  0.267   -1.55  0.00932 0.02     0.0156 
+#>  3 1              3  1.27    -1.13  0.0400  0.0392   0.0807 
+#>  4 1              4  0.0695  -0.701 0.117   0.0577   0.00375
+#>  5 1              5  0.138   -0.275 0.236   0.0755   0.00786
+#>  6 1              6  1.15     0.152 0.339   0.0926   0.0723 
+#>  7 1              7  0.00630  0.578 0.357   0.109    0      
+#>  8 1              8 16.9      1.00  0.292   0.125  Inf      
+#>  9 1              9  0.691    1.43  0.198   0.140    0.0421 
+#> 10 1             10  0.529    1.86  0.126   0.155    0.0319 
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_inverse_weibull.html b/docs/reference/tidy_inverse_weibull.html index 477c4d92..26d8e0b1 100644 --- a/docs/reference/tidy_inverse_weibull.html +++ b/docs/reference/tidy_inverse_weibull.html @@ -193,18 +193,18 @@

Author<

Examples

tidy_inverse_weibull()
 #> # A tibble: 50 × 7
-#>    sim_number     x     y     dx       dy        p     q
-#>    <fct>      <int> <dbl>  <dbl>    <dbl>    <dbl> <dbl>
-#>  1 1              1 0.516 -1.94  0.000590 0        0.270
-#>  2 1              2 5.78  -1.59  0.00277  5.24e-22 1.20 
-#>  3 1              3 0.583 -1.24  0.0104   2.29e-11 0.285
-#>  4 1              4 0.638 -0.894 0.0313   8.06e- 8 0.296
-#>  5 1              5 0.719 -0.544 0.0759   4.79e- 6 0.312
-#>  6 1              6 0.662 -0.195 0.148    5.55e- 5 0.301
-#>  7 1              7 0.563  0.155 0.235    2.84e- 4 0.280
-#>  8 1              8 2.24   0.504 0.304    9.12e- 4 0.544
-#>  9 1              9 0.864  0.854 0.325    2.19e- 3 0.338
-#> 10 1             10 0.395  1.20  0.294    4.32e- 3 0.239
+#>    sim_number     x      y     dx       dy        p     q
+#>    <fct>      <int>  <dbl>  <dbl>    <dbl>    <dbl> <dbl>
+#>  1 1              1  1.14  -3.12  0.000592 0        0.230
+#>  2 1              2  0.721 -1.44  0.0289   5.24e-22 0.203
+#>  3 1              3  0.833  0.240 0.177    2.29e-11 0.211
+#>  4 1              4 26.6    1.92  0.168    8.06e- 8 0.952
+#>  5 1              5  0.926  3.60  0.0604   4.79e- 6 0.217
+#>  6 1              6  3.77   5.28  0.0205   5.55e- 5 0.328
+#>  7 1              7  1.41   6.96  0.0151   2.84e- 4 0.243
+#>  8 1              8  6.73   8.64  0.0130   9.12e- 4 0.409
+#>  9 1              9  0.415 10.3   0.00792  2.19e- 3 0.175
+#> 10 1             10 19.0   12.0   0.00720  4.32e- 3 0.720
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_kurtosis_vec.html b/docs/reference/tidy_kurtosis_vec.html index b7eb5cc1..ab2790ee 100644 --- a/docs/reference/tidy_kurtosis_vec.html +++ b/docs/reference/tidy_kurtosis_vec.html @@ -111,7 +111,7 @@

Author<

Examples

tidy_kurtosis_vec(rnorm(100, 3, 2))
-#> [1] 3.61924
+#> [1] 2.804531
diff --git a/docs/reference/tidy_logistic.html b/docs/reference/tidy_logistic.html index 428ace61..c99df80d 100644 --- a/docs/reference/tidy_logistic.html +++ b/docs/reference/tidy_logistic.html @@ -177,18 +177,18 @@

Author<

Examples

tidy_logistic()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y    dx       dy     p        q
-#>    <fct>      <int>   <dbl> <dbl>    <dbl> <dbl>    <dbl>
-#>  1 1              1  1.30   -7.21 0.000218 0.5     1.35  
-#>  2 1              2  0.953  -6.96 0.000681 0.505   1.11  
-#>  3 1              3 -1.25   -6.72 0.00182  0.510  -0.0467
-#>  4 1              4  0.0612 -6.47 0.00417  0.515   0.598 
-#>  5 1              5  2.65   -6.22 0.00819  0.520   3.03  
-#>  6 1              6  1.88   -5.98 0.0138   0.525   1.83  
-#>  7 1              7  3.03   -5.73 0.0200   0.531 Inf     
-#>  8 1              8  1.65   -5.48 0.0252   0.536   1.62  
-#>  9 1              9  1.24   -5.23 0.0281   0.541   1.30  
-#> 10 1             10 -0.525  -4.99 0.0286   0.546   0.303 
+#>    sim_number     x      y    dx       dy     p         q
+#>    <fct>      <int>  <dbl> <dbl>    <dbl> <dbl>     <dbl>
+#>  1 1              1 -3.49  -7.60 0.000164 0.5   -1.02    
+#>  2 1              2  0.105 -7.34 0.000605 0.505  0.616   
+#>  3 1              3  0.614 -7.09 0.00178  0.510  0.866   
+#>  4 1              4 -0.514 -6.83 0.00422  0.515  0.335   
+#>  5 1              5  2.75  -6.57 0.00809  0.520  2.62    
+#>  6 1              6  1.35  -6.31 0.0127   0.525  1.28    
+#>  7 1              7  1.94  -6.06 0.0167   0.531  1.70    
+#>  8 1              8 -1.29  -5.80 0.0194   0.536 -0.000432
+#>  9 1              9  0.368 -5.54 0.0215   0.541  0.742   
+#> 10 1             10 -4.97  -5.28 0.0241   0.546 -2.13    
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_lognormal.html b/docs/reference/tidy_lognormal.html index a814dfcb..efe58718 100644 --- a/docs/reference/tidy_lognormal.html +++ b/docs/reference/tidy_lognormal.html @@ -176,18 +176,18 @@

Author<

Examples

tidy_lognormal()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y      dx      dy         p      q
-#>    <fct>      <int>  <dbl>   <dbl>   <dbl>     <dbl>  <dbl>
-#>  1 1              1 0.161  -0.833  0.00167 0         0.0804
-#>  2 1              2 0.593  -0.572  0.0180  0.0000497 0.184 
-#>  3 1              3 1.31   -0.311  0.101   0.000690  0.295 
-#>  4 1              4 0.137  -0.0498 0.305   0.00261   0.0685
-#>  5 1              5 0.208   0.211  0.532   0.00611   0.0982
-#>  6 1              6 0.480   0.473  0.600   0.0112    0.163 
-#>  7 1              7 0.862   0.734  0.516   0.0179    0.228 
-#>  8 1              8 0.0968  0.995  0.404   0.0258    0     
-#>  9 1              9 1.37    1.26   0.305   0.0350    0.304 
-#> 10 1             10 0.654   1.52   0.199   0.0451    0.195 
+#>    sim_number     x     y     dx      dy         p     q
+#>    <fct>      <int> <dbl>  <dbl>   <dbl>     <dbl> <dbl>
+#>  1 1              1 0.806 -0.803 0.00136 0         0.186
+#>  2 1              2 1.98  -0.477 0.0223  0.0000497 0.324
+#>  3 1              3 2.21  -0.151 0.147   0.000690  0.349
+#>  4 1              4 0.861  0.174 0.419   0.00261   0.193
+#>  5 1              5 0.559  0.500 0.586   0.00611   0.149
+#>  6 1              6 1.70   0.826 0.514   0.0112    0.293
+#>  7 1              7 1.02   1.15  0.386   0.0179    0.214
+#>  8 1              8 0.323  1.48  0.276   0.0258    0.104
+#>  9 1              9 1.24   1.80  0.213   0.0350    0.241
+#> 10 1             10 1.37   2.13  0.155   0.0451    0.255
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_mixture_density-1.png b/docs/reference/tidy_mixture_density-1.png index 3527ee8f..88bcbaf9 100644 Binary files a/docs/reference/tidy_mixture_density-1.png and b/docs/reference/tidy_mixture_density-1.png differ diff --git a/docs/reference/tidy_mixture_density-2.png b/docs/reference/tidy_mixture_density-2.png index 6d0026b5..75380d6f 100644 Binary files a/docs/reference/tidy_mixture_density-2.png and b/docs/reference/tidy_mixture_density-2.png differ diff --git a/docs/reference/tidy_mixture_density.html b/docs/reference/tidy_mixture_density.html index e4158cfb..02bfe17e 100644 --- a/docs/reference/tidy_mixture_density.html +++ b/docs/reference/tidy_mixture_density.html @@ -106,18 +106,18 @@

Examplesoutput$data #> $dist_tbl #> # A tibble: 150 × 2 -#> x y -#> <int> <dbl> -#> 1 1 -1.46 -#> 2 2 0.377 -#> 3 3 -0.985 -#> 4 4 -0.428 -#> 5 5 1.48 -#> 6 6 0.336 -#> 7 7 -0.203 -#> 8 8 -0.904 -#> 9 9 0.874 -#> 10 10 -1.15 +#> x y +#> <int> <dbl> +#> 1 1 0.333 +#> 2 2 -0.0511 +#> 3 3 -1.03 +#> 4 4 0.509 +#> 5 5 -0.851 +#> 6 6 0.172 +#> 7 7 -0.879 +#> 8 8 -0.624 +#> 9 9 -0.634 +#> 10 10 0.279 #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows #> @@ -125,53 +125,53 @@

Examples#> # A tibble: 150 × 2 #> x y #> <dbl> <dbl> -#> 1 -4.70 0.0000665 -#> 2 -4.60 0.0000975 -#> 3 -4.51 0.000141 -#> 4 -4.41 0.000202 -#> 5 -4.31 0.000287 -#> 6 -4.21 0.000402 -#> 7 -4.12 0.000557 -#> 8 -4.02 0.000767 -#> 9 -3.92 0.00104 -#> 10 -3.83 0.00140 +#> 1 -4.64 0.0000573 +#> 2 -4.53 0.0000843 +#> 3 -4.43 0.000123 +#> 4 -4.33 0.000178 +#> 5 -4.23 0.000254 +#> 6 -4.13 0.000358 +#> 7 -4.03 0.000499 +#> 8 -3.93 0.000689 +#> 9 -3.83 0.000941 +#> 10 -3.73 0.00127 #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows #> #> $input_data #> $input_data$`rnorm(100, 0, 1)` -#> [1] -1.45764633 0.37740395 -0.98525730 -0.42757895 1.48025559 0.33648173 -#> [7] -0.20254759 -0.90369492 0.87356687 -1.14888225 1.98273812 0.45661303 -#> [13] 0.10532920 -0.85134662 -0.23463756 0.85478678 0.47703629 0.39603605 -#> [19] -0.38691229 -0.76559233 0.58349930 1.63975939 0.72256044 -0.44474614 -#> [25] -0.45722427 0.89424396 -0.09054251 0.48127307 -0.50443319 -1.00143786 -#> [31] 0.73671834 0.82206546 0.46452988 -0.60292122 0.63169567 -0.73918488 -#> [37] 0.87847070 0.33961531 0.13057424 -0.46233948 0.83831954 0.78476499 -#> [43] 0.60425347 -1.02450838 -0.73808104 0.37592464 -1.40906362 -2.18148560 -#> [49] 0.26651091 -1.14606077 -0.58491346 0.37524548 -1.33543622 -0.15853331 -#> [55] -1.10406359 -0.01263021 0.58985616 -0.54295103 -0.22075551 0.68520410 -#> [61] -0.31949967 0.17695608 1.42407026 -0.45439977 -1.74227079 0.64187271 -#> [67] -0.67540187 -1.51419692 1.26074451 0.07059006 1.01969872 -1.70322658 -#> [73] -1.73616903 -0.56666579 1.49017136 -1.21986354 0.28965875 -1.30375760 -#> [79] 0.80406191 -0.15991238 0.88963136 1.81352891 -1.00660338 -0.78754881 -#> [85] -1.16911414 1.51560301 -0.06941478 1.75925122 -0.66947848 -1.34217013 -#> [91] -0.40929426 0.08412376 -0.22633675 2.04540415 1.05329515 -0.04635191 -#> [97] -0.20232170 -0.79151517 1.97345656 1.23334517 +#> [1] 0.33342619 -0.05114829 -1.02589077 0.50859412 -0.85105505 0.17182496 +#> [7] -0.87928216 -0.62423926 -0.63372190 0.27889474 -0.11626197 0.42019549 +#> [13] 1.47728634 -1.66744786 -0.63121170 0.97293952 -1.56802951 -1.02692720 +#> [19] -0.69669962 0.34314491 1.15491887 0.57761782 -0.68948748 0.46592641 +#> [25] 0.25631436 0.93835509 1.04507292 0.58419675 0.44774433 0.86763206 +#> [31] -1.38716640 0.90247322 0.03802568 -0.19743450 -0.15585718 0.44554174 +#> [37] -0.25509400 0.61735913 0.20086887 1.80765909 -0.41911107 0.21932587 +#> [43] 0.37960628 -0.61274732 0.80434732 -0.60182400 1.02822689 0.05834868 +#> [49] -1.64055387 -0.05372774 0.65242186 -0.44600212 -1.39207561 0.04146409 +#> [55] 0.08912960 -0.36027981 0.06137096 -1.06299889 0.38376279 -1.31024859 +#> [61] -0.68134020 -0.57123343 0.61758079 1.06798590 0.90954557 0.58497673 +#> [67] 0.45474176 0.14015397 -0.08640400 -0.18171620 -1.13990898 0.31030059 +#> [73] -0.29217276 0.71135816 -0.71979306 0.75314480 -0.06201897 -0.09067604 +#> [79] 0.99650669 -2.14289116 -0.03136940 -0.73987854 -0.11989643 -0.98127744 +#> [85] -0.29344371 1.14717591 0.55248378 -1.18758624 0.92007779 0.51273282 +#> [91] 1.74964419 -0.50026369 2.05555196 -0.76483125 0.53089638 1.07722257 +#> [97] 0.02716953 2.20322460 0.45217447 -0.63219571 #> #> $input_data$`tidy_normal(.mean = 5, .sd = 1)` #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 4.29 1.73 0.000244 0.000000287 4.50 -#> 2 1 2 3.99 1.87 0.000652 0.000000319 4.28 -#> 3 1 3 6.41 2.01 0.00157 0.000000354 5.84 -#> 4 1 4 5.25 2.15 0.00340 0.000000393 5.07 -#> 5 1 5 4.50 2.29 0.00670 0.000000436 4.63 -#> 6 1 6 4.21 2.42 0.0120 0.000000484 4.45 -#> 7 1 7 3.60 2.56 0.0199 0.000000537 3.95 -#> 8 1 8 4.48 2.70 0.0307 0.000000595 4.62 -#> 9 1 9 3.24 2.84 0.0448 0.000000660 3.48 -#> 10 1 10 3.79 2.98 0.0629 0.000000731 4.13 +#> 1 1 1 5.78 0.803 0.000280 0.000000287 5.36 +#> 2 1 2 6.39 0.972 0.000874 0.000000319 5.67 +#> 3 1 3 6.00 1.14 0.00234 0.000000354 5.47 +#> 4 1 4 5.18 1.31 0.00538 0.000000393 5.09 +#> 5 1 5 4.44 1.48 0.0107 0.000000436 4.77 +#> 6 1 6 5.71 1.65 0.0182 0.000000484 5.33 +#> 7 1 7 3.92 1.82 0.0267 0.000000537 4.53 +#> 8 1 8 3.76 1.99 0.0339 0.000000595 4.45 +#> 9 1 9 5.87 2.16 0.0374 0.000000660 5.41 +#> 10 1 10 5.62 2.33 0.0368 0.000000731 5.29 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows #> diff --git a/docs/reference/tidy_multi_dist_autoplot-1.png b/docs/reference/tidy_multi_dist_autoplot-1.png index 1d48737b..8f4ea934 100644 Binary files a/docs/reference/tidy_multi_dist_autoplot-1.png and b/docs/reference/tidy_multi_dist_autoplot-1.png differ diff --git a/docs/reference/tidy_multi_dist_autoplot-2.png b/docs/reference/tidy_multi_dist_autoplot-2.png index fd33f819..bcbbd3ad 100644 Binary files a/docs/reference/tidy_multi_dist_autoplot-2.png and b/docs/reference/tidy_multi_dist_autoplot-2.png differ diff --git a/docs/reference/tidy_multi_single_dist.html b/docs/reference/tidy_multi_single_dist.html index 10dcaecc..1ec97ab3 100644 --- a/docs/reference/tidy_multi_single_dist.html +++ b/docs/reference/tidy_multi_single_dist.html @@ -115,16 +115,16 @@

Examples#> # A tibble: 450 × 8 #> sim_number dist_name x y dx dy p q #> <fct> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 Gaussian c(-1, 1) 1 -0.969 -4.67 0.000280 0.841 -0.726 -#> 2 1 Gaussian c(-1, 1) 2 -0.444 -4.54 0.000857 0.846 -0.399 -#> 3 1 Gaussian c(-1, 1) 3 -0.877 -4.41 0.00226 0.851 -0.672 -#> 4 1 Gaussian c(-1, 1) 4 -3.36 -4.28 0.00517 0.856 -2.48 -#> 5 1 Gaussian c(-1, 1) 5 -1.19 -4.15 0.0103 0.860 -0.856 -#> 6 1 Gaussian c(-1, 1) 6 -0.767 -4.02 0.0177 0.865 -0.605 -#> 7 1 Gaussian c(-1, 1) 7 -0.798 -3.88 0.0268 0.869 -0.624 -#> 8 1 Gaussian c(-1, 1) 8 -1.98 -3.75 0.0358 0.873 -1.30 -#> 9 1 Gaussian c(-1, 1) 9 -2.13 -3.62 0.0426 0.878 -1.39 -#> 10 1 Gaussian c(-1, 1) 10 -1.29 -3.49 0.0459 0.882 -0.910 +#> 1 1 Gaussian c(-1, 1) 1 -0.929 -4.23 0.000432 0.841 -1.09 +#> 2 1 Gaussian c(-1, 1) 2 0.116 -4.09 0.00126 0.846 -0.499 +#> 3 1 Gaussian c(-1, 1) 3 -0.545 -3.95 0.00325 0.851 -0.880 +#> 4 1 Gaussian c(-1, 1) 4 -1.01 -3.81 0.00742 0.856 -1.14 +#> 5 1 Gaussian c(-1, 1) 5 -2.54 -3.67 0.0151 0.860 -2.21 +#> 6 1 Gaussian c(-1, 1) 6 0.513 -3.52 0.0273 0.865 -0.234 +#> 7 1 Gaussian c(-1, 1) 7 -0.992 -3.38 0.0441 0.869 -1.13 +#> 8 1 Gaussian c(-1, 1) 8 0.467 -3.24 0.0643 0.873 -0.267 +#> 9 1 Gaussian c(-1, 1) 9 -0.274 -3.10 0.0851 0.878 -0.729 +#> 10 1 Gaussian c(-1, 1) 10 -0.619 -2.96 0.103 0.882 -0.921 #> # … with 440 more rows #> # ℹ Use `print(n = ...)` to see more rows diff --git a/docs/reference/tidy_negative_binomial.html b/docs/reference/tidy_negative_binomial.html index ccc99ef1..ebd77e63 100644 --- a/docs/reference/tidy_negative_binomial.html +++ b/docs/reference/tidy_negative_binomial.html @@ -163,18 +163,18 @@

Author<

Examples

tidy_negative_binomial()
 #> # A tibble: 50 × 7
-#>    sim_number     x     y       dx       dy     p     q
-#>    <fct>      <int> <int>    <dbl>    <dbl> <dbl> <dbl>
-#>  1 1              1     1 -10.1    0.000211   0.1     0
-#>  2 1              2     1  -8.70   0.000733   0.1     0
-#>  3 1              3    13  -7.27   0.00214    0.1     2
-#>  4 1              4     4  -5.83   0.00531    0.1     0
-#>  5 1              5    19  -4.40   0.0112     0.1     4
-#>  6 1              6     2  -2.97   0.0201     0.1     0
-#>  7 1              7    10  -1.53   0.0311     0.1     2
-#>  8 1              8     0  -0.0970 0.0419     0.1     0
-#>  9 1              9     9   1.34   0.0498     0.1     1
-#> 10 1             10    14   2.77   0.0531     0.1     3
+#>    sim_number     x     y     dx       dy     p     q
+#>    <fct>      <int> <int>  <dbl>    <dbl> <dbl> <dbl>
+#>  1 1              1     2 -8.98  0.000155   0.1     0
+#>  2 1              2     2 -7.56  0.000633   0.1     0
+#>  3 1              3     7 -6.13  0.00210    0.1     1
+#>  4 1              4     0 -4.70  0.00568    0.1     0
+#>  5 1              5    28 -3.27  0.0126     0.1     7
+#>  6 1              6    20 -1.84  0.0234     0.1     4
+#>  7 1              7     6 -0.416 0.0365     0.1     1
+#>  8 1              8     8  1.01  0.0487     0.1     1
+#>  9 1              9     8  2.44  0.0569     0.1     1
+#> 10 1             10    18  3.87  0.0592     0.1     4
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_normal.html b/docs/reference/tidy_normal.html index 9d451dd6..8ead8eaa 100644 --- a/docs/reference/tidy_normal.html +++ b/docs/reference/tidy_normal.html @@ -177,18 +177,18 @@

Author<

Examples

tidy_normal()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y    dx       dy     p        q
-#>    <fct>      <int>   <dbl> <dbl>    <dbl> <dbl>    <dbl>
-#>  1 1              1  0.541  -3.23 0.000263 0.5     0.532 
-#>  2 1              2  0.0293 -3.10 0.000693 0.508   0.170 
-#>  3 1              3  1.25   -2.98 0.00165  0.516   1.22  
-#>  4 1              4 -0.480  -2.86 0.00358  0.524  -0.169 
-#>  5 1              5  0.208  -2.74 0.00708  0.533   0.292 
-#>  6 1              6 -0.411  -2.61 0.0128   0.541  -0.123 
-#>  7 1              7 -0.271  -2.49 0.0214   0.549  -0.0297
-#>  8 1              8  0.496  -2.37 0.0329   0.557   0.498 
-#>  9 1              9  1.05   -2.25 0.0471   0.565   0.978 
-#> 10 1             10  1.67   -2.12 0.0630   0.573 Inf     
+#>    sim_number     x      y    dx       dy     p      q
+#>    <fct>      <int>  <dbl> <dbl>    <dbl> <dbl>  <dbl>
+#>  1 1              1  1.12  -3.76 0.000250 0.5    0.651
+#>  2 1              2 -0.436 -3.61 0.000787 0.508 -0.156
+#>  3 1              3  0.867 -3.46 0.00210  0.516  0.504
+#>  4 1              4 -0.934 -3.31 0.00472  0.524 -0.410
+#>  5 1              5  0.696 -3.16 0.00898  0.533  0.411
+#>  6 1              6  0.119 -3.01 0.0145   0.541  0.117
+#>  7 1              7 -1.37  -2.87 0.0199   0.549 -0.655
+#>  8 1              8 -1.02  -2.72 0.0237   0.557 -0.458
+#>  9 1              9 -0.693 -2.57 0.0251   0.565 -0.285
+#> 10 1             10 -0.482 -2.42 0.0252   0.573 -0.179
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_paralogistic.html b/docs/reference/tidy_paralogistic.html index a56e8167..0de73054 100644 --- a/docs/reference/tidy_paralogistic.html +++ b/docs/reference/tidy_paralogistic.html @@ -187,18 +187,18 @@

Author<

Examples

tidy_paralogistic()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y      dx       dy      p       q
-#>    <fct>      <int>  <dbl>   <dbl>    <dbl>  <dbl>   <dbl>
-#>  1 1              1 1.52   -2.50   0.000781 0      0.0632 
-#>  2 1              2 1.05   -1.88   0.00673  0.0200 0.0427 
-#>  3 1              3 0.0441 -1.26   0.0352   0.0392 0.00130
-#>  4 1              4 8.06   -0.639  0.114    0.0577 0.467  
-#>  5 1              5 0.505  -0.0196 0.232    0.0755 0.0199 
-#>  6 1              6 0.908   0.599  0.301    0.0926 0.0367 
-#>  7 1              7 1.01    1.22   0.253    0.109  0.0409 
-#>  8 1              8 0.628   1.84   0.148    0.125  0.0250 
-#>  9 1              9 0.583   2.46   0.0808   0.140  0.0231 
-#> 10 1             10 9.04    3.08   0.0594   0.155  0.554  
+#>    sim_number     x       y     dx         dy      p        q
+#>    <fct>      <int>   <dbl>  <dbl>      <dbl>  <dbl>    <dbl>
+#>  1 1              1 0.284   -2.48  0.00117    0      0.00216 
+#>  2 1              2 2.48     0.247 0.269      0.0200 0.0196  
+#>  3 1              3 0.576    2.97  0.0576     0.0392 0.00446 
+#>  4 1              4 0.729    5.69  0.0115     0.0577 0.00566 
+#>  5 1              5 0.00643  8.41  0.0000119  0.0755 0       
+#>  6 1              6 0.415   11.1   0.00800    0.0926 0.00320 
+#>  7 1              7 0.0787  13.9   0.00274    0.109  0.000563
+#>  8 1              8 0.308   16.6   0.00306    0.125  0.00236 
+#>  9 1              9 3.45    19.3   0.00781    0.140  0.0276  
+#> 10 1             10 1.30    22.0   0.00000630 0.155  0.0102  
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
 
diff --git a/docs/reference/tidy_pareto.html b/docs/reference/tidy_pareto.html
index b61a8979..3621d8ae 100644
--- a/docs/reference/tidy_pareto.html
+++ b/docs/reference/tidy_pareto.html
@@ -181,16 +181,16 @@ 
Examples#> # A tibble: 50 × 7
 #>    sim_number     x        y        dx     dy     p         q
 #>    <fct>      <int>    <dbl>     <dbl>  <dbl> <dbl>     <dbl>
-#>  1 1              1 0.0148   -0.0106    0.197 0     0.00592  
-#>  2 1              2 0.00477  -0.00947   0.511 0.844 0.00149  
-#>  3 1              3 0.000380 -0.00834   1.21  0.967 0.0000619
-#>  4 1              4 0.000407 -0.00722   2.61  0.992 0.0000700
-#>  5 1              5 0.00554  -0.00610   5.15  0.997 0.00177  
-#>  6 1              6 0.00304  -0.00498   9.31  0.999 0.000901 
-#>  7 1              7 0.00669  -0.00386  15.4   1.00  0.00219  
-#>  8 1              8 0.00222  -0.00274  23.4   1.00  0.000634 
-#>  9 1              9 0.0180   -0.00162  32.8   1.00  0.00790  
-#> 10 1             10 0.00438  -0.000497 42.3   1.00  0.00136  
+#>  1 1              1 0.00551  -0.00675   0.223 0     0.000998 
+#>  2 1              2 0.00464  -0.00533   1.30  0.844 0.000825 
+#>  3 1              3 0.000599 -0.00390   5.35  0.967 0.0000675
+#>  4 1              4 0.000542 -0.00247  15.7   0.992 0.0000574
+#>  5 1              5 0.00868  -0.00104  33.4   0.997 0.00165  
+#>  6 1              6 0.00682   0.000384 53.5   0.999 0.00126  
+#>  7 1              7 0.00541   0.00181  67.6   1.00  0.000977 
+#>  8 1              8 0.00421   0.00324  72.1   1.00  0.000742 
+#>  9 1              9 0.00484   0.00467  69.9   1.00  0.000865 
+#> 10 1             10 0.00425   0.00609  64.7   1.00  0.000750 
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_pareto1.html b/docs/reference/tidy_pareto1.html index e20ffbef..8af70809 100644 --- a/docs/reference/tidy_pareto1.html +++ b/docs/reference/tidy_pareto1.html @@ -179,18 +179,18 @@

Author<

Examples

tidy_pareto1()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y     dx       dy     p      q
-#>    <fct>      <int>  <dbl>  <dbl>    <dbl> <dbl>  <dbl>
-#>  1 1              1   1.03  -1.86 3.09e- 3     0   1.00
-#>  2 1              2   1.47  12.2  3.46e- 3     0   1.00
-#>  3 1              3   1.88  26.3  3.51e- 3     0   1.00
-#>  4 1              4   5.76  40.4  0            0   1.01
-#>  5 1              5   1.91  54.5  0            0   1.00
-#>  6 1              6   1.48  68.6  1.82e-18     0   1.00
-#>  7 1              7   7.70  82.6  1.49e-15     0   1.01
-#>  8 1              8   3.64  96.7  7.14e-10     0   1.00
-#>  9 1              9 685.   111.   2.12e-18     0 Inf   
-#> 10 1             10   1.44 125.   0            0   1.00
+#>    sim_number     x     y    dx           dy     p     q
+#>    <fct>      <int> <dbl> <dbl>        <dbl> <dbl> <dbl>
+#>  1 1              1  1.81 -4.26 0.000920         0  1.00
+#>  2 1              2  1.51  2.38 0.133            0  1.00
+#>  3 1              3  2.80  9.02 0.0102           0  1.01
+#>  4 1              4 20.2  15.7  0.0111           0  1.06
+#>  5 1              5  1.03 22.3  0.00672          0  1   
+#>  6 1              6  1.10 28.9  0.0000308        0  1.00
+#>  7 1              7  1.25 35.6  0.00428          0  1.00
+#>  8 1              8 13.2  42.2  0.00186          0  1.04
+#>  9 1              9  1.69 48.8  0.0000000158     0  1.00
+#> 10 1             10  1.46 55.5  0                0  1.00
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/tidy_poisson.html b/docs/reference/tidy_poisson.html index eaee5cd4..ea50a11c 100644 --- a/docs/reference/tidy_poisson.html +++ b/docs/reference/tidy_poisson.html @@ -157,16 +157,16 @@

Examples#> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> <fct> <int> <int> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 3 -1.49 0.00253 0.368 2 -#> 2 1 2 2 -1.35 0.00572 0.368 1 -#> 3 1 3 0 -1.21 0.0119 0.368 0 -#> 4 1 4 2 -1.06 0.0229 0.368 1 -#> 5 1 5 0 -0.922 0.0406 0.368 0 -#> 6 1 6 2 -0.779 0.0664 0.368 1 -#> 7 1 7 1 -0.637 0.100 0.368 0 -#> 8 1 8 0 -0.494 0.140 0.368 0 -#> 9 1 9 3 -0.352 0.181 0.368 2 -#> 10 1 10 4 -0.209 0.219 0.368 Inf +#> 1 1 1 1 -1.34 0.00400 0.368 0 +#> 2 1 2 1 -1.21 0.00952 0.368 0 +#> 3 1 3 0 -1.07 0.0206 0.368 0 +#> 4 1 4 2 -0.933 0.0408 0.368 1 +#> 5 1 5 1 -0.797 0.0734 0.368 0 +#> 6 1 6 0 -0.660 0.121 0.368 0 +#> 7 1 7 1 -0.524 0.181 0.368 0 +#> 8 1 8 1 -0.387 0.248 0.368 0 +#> 9 1 9 1 -0.251 0.310 0.368 0 +#> 10 1 10 0 -0.115 0.357 0.368 0 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows diff --git a/docs/reference/tidy_random_walk.html b/docs/reference/tidy_random_walk.html index 2c1ad576..28d4724e 100644 --- a/docs/reference/tidy_random_walk.html +++ b/docs/reference/tidy_random_walk.html @@ -133,18 +133,18 @@

Examples
tidy_normal(.sd = .1, .num_sims = 25) %>%
   tidy_random_walk()
 #> # A tibble: 1,250 × 8
-#>    sim_number     x        y     dx      dy     p       q random_walk_value
-#>    <fct>      <int>    <dbl>  <dbl>   <dbl> <dbl>   <dbl>             <dbl>
-#>  1 1              1  0.0948  -0.313 0.00303 0.5    0.0444            0.0948
-#>  2 1              2  0.0503  -0.299 0.00804 0.581  0.0166            0.150 
-#>  3 1              3  0.0727  -0.286 0.0193  0.658  0.0303            0.233 
-#>  4 1              4 -0.128   -0.272 0.0423  0.730 -0.107             0.0759
-#>  5 1              5  0.0894  -0.258 0.0844  0.793  0.0409            0.172 
-#>  6 1              6  0.137   -0.244 0.155   0.846  0.0747            0.333 
-#>  7 1              7 -0.121   -0.231 0.263   0.890 -0.100             0.171 
-#>  8 1              8 -0.0913  -0.217 0.417   0.923 -0.0741            0.0643
-#>  9 1              9 -0.0903  -0.203 0.623   0.949 -0.0733           -0.0318
-#> 10 1             10  0.00239 -0.190 0.882   0.967 -0.0120           -0.0295
+#>    sim_number     x        y     dx      dy     p        q random_walk_value
+#>    <fct>      <int>    <dbl>  <dbl>   <dbl> <dbl>    <dbl>             <dbl>
+#>  1 1              1  0.0110  -0.389 0.00194 0.5    0.0106            0.0110 
+#>  2 1              2  0.151   -0.374 0.00495 0.581  0.0976            0.164  
+#>  3 1              3  0.0593  -0.358 0.0115  0.658  0.0368            0.233  
+#>  4 1              4  0.225   -0.343 0.0240  0.730  0.234             0.510  
+#>  5 1              5 -0.114   -0.327 0.0458  0.793 -0.0585            0.337  
+#>  6 1              6 -0.171   -0.312 0.0803  0.846 -0.0988            0.109  
+#>  7 1              7 -0.114   -0.296 0.131   0.890 -0.0584           -0.0179 
+#>  8 1              8  0.00830 -0.281 0.201   0.923  0.00919          -0.00977
+#>  9 1              9  0.0477  -0.265 0.295   0.949  0.0303            0.0374 
+#> 10 1             10  0.0606  -0.250 0.421   0.967  0.0375            0.100  
 #> # … with 1,240 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
 
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diff --git a/docs/reference/tidy_scale_zero_one_vec-1.png b/docs/reference/tidy_scale_zero_one_vec-1.png
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diff --git a/docs/reference/tidy_skewness_vec.html b/docs/reference/tidy_skewness_vec.html
index 0fca813d..621ed92b 100644
--- a/docs/reference/tidy_skewness_vec.html
+++ b/docs/reference/tidy_skewness_vec.html
@@ -108,7 +108,7 @@ 
Author<
     

     
Examples

     
tidy_skewness_vec(rnorm(100, 3, 2))
-#> [1] 0.09061656
+#> [1] -0.08732319
 
 

     

diff --git a/docs/reference/tidy_t.html b/docs/reference/tidy_t.html
index d2a9066d..d11ef7ae 100644
--- a/docs/reference/tidy_t.html
+++ b/docs/reference/tidy_t.html
@@ -175,18 +175,18 @@ 
Author<
     
Examples

     
tidy_t()
 #> # A tibble: 50 × 7
-#>    sim_number     x        y    dx          dy     p       q
-#>    <fct>      <int>    <dbl> <dbl>       <dbl> <dbl>   <dbl>
-#>  1 1              1  -1.07   -36.4 0.000178    0.5    0.869 
-#>  2 1              2 -11.8    -35.4 0.00796     0.506 -0.0147
-#>  3 1              3   2.87   -34.4 0.0111      0.513  1.50  
-#>  4 1              4   0.0326 -33.4 0.000469    0.519  1.01  
-#>  5 1              5  -0.581  -32.4 0.000000617 0.526  0.929 
-#>  6 1              6   1.41   -31.4 0.000000411 0.532  1.22  
-#>  7 1              7   3.83   -30.3 0.000362    0.539  1.73  
-#>  8 1              8  -0.324  -29.3 0.0103      0.545  0.962 
-#>  9 1              9  -2.16   -28.3 0.00874     0.552  0.747 
-#> 10 1             10   0.788  -27.3 0.000224    0.558  1.12  
+#>    sim_number     x        y     dx       dy     p     q
+#>    <fct>      <int>    <dbl>  <dbl>    <dbl> <dbl> <dbl>
+#>  1 1              1  0.226   -22.5  2.86e- 3 0.5   -13.9
+#>  2 1              2  1.11     -3.65 3.41e- 2 0.506 -13.3
+#>  3 1              3 -0.167    15.2  9.01e-14 0.513 -14.2
+#>  4 1              4  0.323    34.0  5.49e- 3 0.519 -13.8
+#>  5 1              5 -0.00455  52.9  0        0.526 -14.0
+#>  6 1              6 -2.69     71.7  0        0.532 -16.1
+#>  7 1              7  7.74     90.6  2.73e-18 0.539 -10.2
+#>  8 1              8 -0.358   109.   2.88e-20 0.545 -14.3
+#>  9 1              9  0.866   128.   0        0.552 -13.5
+#> 10 1             10  0.141   147.   2.64e-19 0.558 -14.0
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
 

diff --git a/docs/reference/tidy_uniform.html b/docs/reference/tidy_uniform.html
index d9108a64..319d45d5 100644
--- a/docs/reference/tidy_uniform.html
+++ b/docs/reference/tidy_uniform.html
@@ -176,18 +176,18 @@ 
Author<
     
Examples

     
tidy_uniform()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y      dx      dy      p       q
-#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>   <dbl>
-#>  1 1              1 0.938  -0.339  0.00213 0      0.946  
-#>  2 1              2 0.641  -0.305  0.00512 0.0204 0.643  
-#>  3 1              3 0.910  -0.270  0.0113  0.0408 0.917  
-#>  4 1              4 0.375  -0.236  0.0230  0.0612 0.373  
-#>  5 1              5 0.206  -0.202  0.0431  0.0816 0.200  
-#>  6 1              6 0.380  -0.168  0.0749  0.102  0.378  
-#>  7 1              7 0.830  -0.133  0.121   0.122  0.836  
-#>  8 1              8 0.643  -0.0992 0.182   0.143  0.646  
-#>  9 1              9 0.0131 -0.0649 0.256   0.163  0.00418
-#> 10 1             10 0.688  -0.0307 0.340   0.184  0.691  
+#>    sim_number     x       y      dx      dy      p      q
+#>    <fct>      <int>   <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
+#>  1 1              1 0.0539  -0.377  0.00168 0      0.0517
+#>  2 1              2 0.982   -0.341  0.00404 0.0204 0.996 
+#>  3 1              3 0.854   -0.306  0.00899 0.0408 0.866 
+#>  4 1              4 0.903   -0.270  0.0187  0.0612 0.916 
+#>  5 1              5 0.477   -0.235  0.0361  0.0816 0.483 
+#>  6 1              6 0.151   -0.199  0.0652  0.102  0.150 
+#>  7 1              7 0.368   -0.163  0.110   0.122  0.371 
+#>  8 1              8 0.367   -0.128  0.174   0.143  0.371 
+#>  9 1              9 0.202   -0.0923 0.258   0.163  0.202 
+#> 10 1             10 0.00306 -0.0568 0.359   0.184  0     
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
 

diff --git a/docs/reference/tidy_weibull.html b/docs/reference/tidy_weibull.html
index eb4628a6..3db9e3c4 100644
--- a/docs/reference/tidy_weibull.html
+++ b/docs/reference/tidy_weibull.html
@@ -177,18 +177,18 @@ 
Author<
     
Examples

     
tidy_weibull()
 #> # A tibble: 50 × 7
-#>    sim_number     x     y      dx      dy      p      q
-#>    <fct>      <int> <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
-#>  1 1              1 2.53  -1.37   0.00130 0      0.557 
-#>  2 1              2 2.15  -1.20   0.00424 0.0202 0.450 
-#>  3 1              3 0.505 -1.02   0.0120  0.0400 0.0867
-#>  4 1              4 1.95  -0.843  0.0299  0.0594 0.397 
-#>  5 1              5 0.952 -0.666  0.0646  0.0784 0.173 
-#>  6 1              6 0.177 -0.489  0.122   0.0970 0.0277
-#>  7 1              7 0.139 -0.312  0.203   0.115  0.0210
-#>  8 1              8 2.23  -0.135  0.297   0.133  0.472 
-#>  9 1              9 1.17   0.0414 0.385   0.151  0.217 
-#> 10 1             10 1.26   0.218  0.447   0.168  0.238 
+#>    sim_number     x       y      dx      dy      p      q
+#>    <fct>      <int>   <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
+#>  1 1              1 0.223   -1.13   0.00121 0      0.0675
+#>  2 1              2 0.245   -1.02   0.00315 0.0202 0.0745
+#>  3 1              3 0.289   -0.902  0.00747 0.0400 0.0886
+#>  4 1              4 0.0587  -0.787  0.0163  0.0594 0.0170
+#>  5 1              5 0.539   -0.671  0.0326  0.0784 0.173 
+#>  6 1              6 0.00145 -0.556  0.0600  0.0970 0     
+#>  7 1              7 1.02    -0.440  0.102   0.115  0.357 
+#>  8 1              8 0.315   -0.325  0.159   0.133  0.0970
+#>  9 1              9 0.223   -0.209  0.231   0.151  0.0675
+#> 10 1             10 0.512   -0.0934 0.310   0.168  0.163 
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
 

diff --git a/docs/reference/tidy_zero_truncated_poisson.html b/docs/reference/tidy_zero_truncated_poisson.html
index 96b2b5b0..93092bf1 100644
--- a/docs/reference/tidy_zero_truncated_poisson.html
+++ b/docs/reference/tidy_zero_truncated_poisson.html
@@ -159,16 +159,16 @@ 
Examples#> # A tibble: 50 × 7
 #>    sim_number     x     y     dx      dy     p     q
 #>    <fct>      <int> <int>  <dbl>   <dbl> <dbl> <dbl>
-#>  1 1              1     1 0.0923 0.00890     0     1
-#>  2 1              2     2 0.191  0.0223      0     1
-#>  3 1              3     2 0.289  0.0504      0     1
-#>  4 1              4     1 0.387  0.102       0     1
-#>  5 1              5     1 0.485  0.187       0     1
-#>  6 1              6     1 0.584  0.308       0     1
-#>  7 1              7     1 0.682  0.456       0     1
-#>  8 1              8     3 0.780  0.608       0     2
-#>  9 1              9     2 0.879  0.730       0     1
-#> 10 1             10     3 0.977  0.790       0     2
+#>  1 1              1     1 0.0786 0.00875     0     1
+#>  2 1              2     1 0.177  0.0218      0     1
+#>  3 1              3     2 0.276  0.0489      0     1
+#>  4 1              4     2 0.375  0.0989      0     1
+#>  5 1              5     2 0.474  0.180       0     1
+#>  6 1              6     3 0.573  0.297       0     2
+#>  7 1              7     1 0.672  0.441       0     1
+#>  8 1              8     2 0.770  0.590       0     1
+#>  9 1              9     1 0.869  0.712       0     1
+#> 10 1             10     1 0.968  0.776       0     1
 #> # … with 40 more rows
 #> # ℹ Use `print(n = ...)` to see more rows
diff --git a/docs/reference/util_beta_param_estimate-1.png b/docs/reference/util_beta_param_estimate-1.png index 0c02f45f..1d0b9c9f 100644 Binary files a/docs/reference/util_beta_param_estimate-1.png and b/docs/reference/util_beta_param_estimate-1.png differ diff --git a/docs/reference/util_beta_param_estimate.html b/docs/reference/util_beta_param_estimate.html index 3b012dab..c5eada1e 100644 --- a/docs/reference/util_beta_param_estimate.html +++ b/docs/reference/util_beta_param_estimate.html @@ -177,9 +177,9 @@

Examples#> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Beta 50 0.199 0.991 0.650 0.0419 Bayes 32.5 17.5 1.86 -#> 2 Beta 50 0.199 0.991 0.650 0.0419 NIST_MME 2.88 1.55 1.86 -#> 3 Beta 50 0.199 0.991 0.650 0.0419 EnvStats… 2.95 1.59 1.86 +#> 1 Beta 50 0.190 0.997 0.675 0.0523 Bayes 33.7 16.3 2.07 +#> 2 Beta 50 0.190 0.997 0.675 0.0523 NIST_MME 2.16 1.04 2.07 +#> 3 Beta 50 0.190 0.997 0.675 0.0523 EnvStats… 2.22 1.07 2.07 #> # … with abbreviated variable name ¹​shape_ratio diff --git a/docs/reference/util_beta_stats_tbl.html b/docs/reference/util_beta_stats_tbl.html index a70e941a..317c1faa 100644 --- a/docs/reference/util_beta_stats_tbl.html +++ b/docs/reference/util_beta_stats_tbl.html @@ -133,10 +133,10 @@

Examples#> $ coeff_var <dbl> 0.5773503 #> $ skewness <dbl> 0 #> $ kurtosis <lgl> NA -#> $ computed_std_skew <dbl> 0.01144016 -#> $ computed_std_kurt <dbl> 1.96805 -#> $ ci_lo <dbl> 0.04156415 -#> $ ci_hi <dbl> 0.9507906 +#> $ computed_std_skew <dbl> 0.2541739 +#> $ computed_std_kurt <dbl> 2.124569 +#> $ ci_lo <dbl> 0.01215601 +#> $ ci_hi <dbl> 0.9050219 diff --git a/docs/reference/util_binomial_param_estimate-1.png b/docs/reference/util_binomial_param_estimate-1.png index 4d09db8c..8b6e51b1 100644 Binary files a/docs/reference/util_binomial_param_estimate-1.png and b/docs/reference/util_binomial_param_estimate-1.png differ diff --git a/docs/reference/util_binomial_param_estimate.html b/docs/reference/util_binomial_param_estimate.html index d2860a30..23ccabee 100644 --- a/docs/reference/util_binomial_param_estimate.html +++ b/docs/reference/util_binomial_param_estimate.html @@ -149,7 +149,7 @@

Examples#> # A tibble: 1 × 10 #> dist_type samp_size min max mean variance method prob size shape…¹ #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <int> <dbl> -#> 1 Binomial 50 0 1 0.14 0.123 EnvStats_M… 0.14 50 0.0028 +#> 1 Binomial 50 0 1 0.12 0.108 EnvStats_M… 0.12 50 0.0024 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% diff --git a/docs/reference/util_cauchy_param_estimate-1.png b/docs/reference/util_cauchy_param_estimate-1.png index 6d2c8318..f58c5387 100644 Binary files a/docs/reference/util_cauchy_param_estimate-1.png and b/docs/reference/util_cauchy_param_estimate-1.png differ diff --git a/docs/reference/util_cauchy_param_estimate.html b/docs/reference/util_cauchy_param_estimate.html index bea9cf7b..302b8333 100644 --- a/docs/reference/util_cauchy_param_estimate.html +++ b/docs/reference/util_cauchy_param_estimate.html @@ -134,7 +134,7 @@

Examples#> # A tibble: 1 × 8 #> dist_type samp_size min max method location scale ratio #> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Cauchy 50 -72.2 339. MASS -0.0681 2.65 -0.0257 +#> 1 Cauchy 50 -20.3 5.93 MASS -0.0909 1.35 -0.0673 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_cauchy_stats_tbl.html b/docs/reference/util_cauchy_stats_tbl.html index 35a6f462..10c78b9e 100644 --- a/docs/reference/util_cauchy_stats_tbl.html +++ b/docs/reference/util_cauchy_stats_tbl.html @@ -132,10 +132,10 @@

Examples#> $ coeff_var <chr> "undefined" #> $ skewness <dbl> 0 #> $ kurtosis <chr> "undefined" -#> $ computed_std_skew <dbl> 2.03255 -#> $ computed_std_kurt <dbl> 13.14494 -#> $ ci_lo <dbl> -12.21519 -#> $ ci_hi <dbl> 17.1068 +#> $ computed_std_skew <dbl> 2.361671 +#> $ computed_std_kurt <dbl> 19.553 +#> $ ci_lo <dbl> -14.59186 +#> $ ci_hi <dbl> 4.52635 diff --git a/docs/reference/util_chisquare_stats_tbl.html b/docs/reference/util_chisquare_stats_tbl.html index 684b69ec..98129df9 100644 --- a/docs/reference/util_chisquare_stats_tbl.html +++ b/docs/reference/util_chisquare_stats_tbl.html @@ -131,10 +131,10 @@

Examples#> $ coeff_var <dbl> 1.414214 #> $ skewness <dbl> 2.828427 #> $ kurtosis <dbl> 15 -#> $ computed_std_skew <dbl> 2.608379 -#> $ computed_std_kurt <dbl> 10.17601 -#> $ ci_lo <dbl> 0.0388085 -#> $ ci_hi <dbl> 7.210262 +#> $ computed_std_skew <dbl> 1.369179 +#> $ computed_std_kurt <dbl> 4.203692 +#> $ ci_lo <dbl> 0.001979251 +#> $ ci_hi <dbl> 8.331546 diff --git a/docs/reference/util_exponential_param_estimate-1.png b/docs/reference/util_exponential_param_estimate-1.png index cc7a124e..cb9eac25 100644 Binary files a/docs/reference/util_exponential_param_estimate-1.png and b/docs/reference/util_exponential_param_estimate-1.png differ diff --git a/docs/reference/util_exponential_param_estimate.html b/docs/reference/util_exponential_param_estimate.html index 60b2c83e..4a745cc3 100644 --- a/docs/reference/util_exponential_param_estimate.html +++ b/docs/reference/util_exponential_param_estimate.html @@ -137,7 +137,7 @@

Examples#> # A tibble: 1 × 8 #> dist_type samp_size min max mean variance method rate #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> -#> 1 Exponential 50 0.340 43.6 10.3 113. NIST_MME 0.0969 +#> 1 Exponential 50 0.199 38.2 10.9 83.1 NIST_MME 0.0916 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_exponential_stats_tbl.html b/docs/reference/util_exponential_stats_tbl.html index cfb68c13..664c6264 100644 --- a/docs/reference/util_exponential_stats_tbl.html +++ b/docs/reference/util_exponential_stats_tbl.html @@ -134,10 +134,10 @@

Examples#> $ coeff_var <dbl> 1 #> $ skewness <dbl> 2 #> $ kurtosis <dbl> 9 -#> $ computed_std_skew <dbl> 3.937832 -#> $ computed_std_kurt <dbl> 22.3348 -#> $ ci_lo <dbl> 0.05862891 -#> $ ci_hi <dbl> 3.370082 +#> $ computed_std_skew <dbl> 1.606079 +#> $ computed_std_kurt <dbl> 5.649964 +#> $ ci_lo <dbl> 0.03998032 +#> $ ci_hi <dbl> 2.62225 diff --git a/docs/reference/util_f_stats_tbl.html b/docs/reference/util_f_stats_tbl.html index 892fb266..93a2d4a7 100644 --- a/docs/reference/util_f_stats_tbl.html +++ b/docs/reference/util_f_stats_tbl.html @@ -131,10 +131,10 @@

Examples#> $ coeff_var <chr> "undefined" #> $ skewness <chr> "undefined" #> $ kurtosis <chr> "Not computed" -#> $ computed_std_skew <dbl> 6.360531 -#> $ computed_std_kurt <dbl> 43.20686 -#> $ ci_lo <dbl> 0.005427014 -#> $ ci_hi <dbl> 200.4485 +#> $ computed_std_skew <dbl> 6.333812 +#> $ computed_std_kurt <dbl> 42.96724 +#> $ ci_lo <dbl> 0.004044745 +#> $ ci_hi <dbl> 184.3791 diff --git a/docs/reference/util_gamma_param_estimate-1.png b/docs/reference/util_gamma_param_estimate-1.png index b47d5a01..45fc98e1 100644 Binary files a/docs/reference/util_gamma_param_estimate-1.png and b/docs/reference/util_gamma_param_estimate-1.png differ diff --git a/docs/reference/util_gamma_param_estimate.html b/docs/reference/util_gamma_param_estimate.html index 07b3a89c..0e8cea82 100644 --- a/docs/reference/util_gamma_param_estimate.html +++ b/docs/reference/util_gamma_param_estimate.html @@ -137,9 +137,9 @@

Examples#> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape scale shape…¹ #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Gamma 50 0.00150 1.31 0.301 0.264 NIST_MME 1.30 0.232 5.61 -#> 2 Gamma 50 0.00150 1.31 0.301 0.264 EnvStats… 1.27 0.232 5.50 -#> 3 Gamma 50 0.00150 1.31 0.301 0.264 EnvStats… 1.24 0.232 5.33 +#> 1 Gamma 50 0.00446 1.58 0.335 0.316 NIST_MME 1.12 0.299 3.74 +#> 2 Gamma 50 0.00446 1.58 0.335 0.316 EnvStats… 1.10 0.299 3.67 +#> 3 Gamma 50 0.00446 1.58 0.335 0.316 EnvStats… 1.07 0.299 3.56 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% diff --git a/docs/reference/util_gamma_stats_tbl.html b/docs/reference/util_gamma_stats_tbl.html index fc8d6b45..d3fa686d 100644 --- a/docs/reference/util_gamma_stats_tbl.html +++ b/docs/reference/util_gamma_stats_tbl.html @@ -133,10 +133,10 @@

Examples#> $ coeff_var <dbl> 1 #> $ skewness <dbl> 2 #> $ kurtosis <dbl> 9 -#> $ computed_std_skew <dbl> 1.712431 -#> $ computed_std_kurt <dbl> 6.524924 -#> $ ci_lo <dbl> 0.005972779 -#> $ ci_hi <dbl> 1.119421 +#> $ computed_std_skew <dbl> 2.522683 +#> $ computed_std_kurt <dbl> 11.60953 +#> $ ci_lo <dbl> 0.01712874 +#> $ ci_hi <dbl> 1.022674 diff --git a/docs/reference/util_geometric_param_estimate-1.png b/docs/reference/util_geometric_param_estimate-1.png index 647ebc46..b986cefb 100644 Binary files a/docs/reference/util_geometric_param_estimate-1.png and b/docs/reference/util_geometric_param_estimate-1.png differ diff --git a/docs/reference/util_geometric_param_estimate.html b/docs/reference/util_geometric_param_estimate.html index 8ff4b9c2..40dc0dbc 100644 --- a/docs/reference/util_geometric_param_estimate.html +++ b/docs/reference/util_geometric_param_estimate.html @@ -139,8 +139,8 @@

Examples#> # A tibble: 2 × 9 #> dist_type samp_size min max mean variance sum_x method shape #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> -#> 1 Geometric 50 0 24 6.24 31.9 312 EnvStats_MME 0.138 -#> 2 Geometric 50 0 24 6.24 31.9 312 EnvStats_MVUE 0.136 +#> 1 Geometric 50 0 30 6.76 40.4 338 EnvStats_MME 0.129 +#> 2 Geometric 50 0 30 6.76 40.4 338 EnvStats_MVUE 0.127 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_hypergeometric_param_estimate-1.png b/docs/reference/util_hypergeometric_param_estimate-1.png index d577675a..2af0cd0e 100644 Binary files a/docs/reference/util_hypergeometric_param_estimate-1.png and b/docs/reference/util_hypergeometric_param_estimate-1.png differ diff --git a/docs/reference/util_logistic_param_estimate-1.png b/docs/reference/util_logistic_param_estimate-1.png index ed047fc1..2bf40026 100644 Binary files a/docs/reference/util_logistic_param_estimate-1.png and b/docs/reference/util_logistic_param_estimate-1.png differ diff --git a/docs/reference/util_logistic_param_estimate.html b/docs/reference/util_logistic_param_estimate.html index ab17c778..67b2c33f 100644 --- a/docs/reference/util_logistic_param_estimate.html +++ b/docs/reference/util_logistic_param_estimate.html @@ -164,9 +164,9 @@

Examples#> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Logistic 50 -8.65 5.85 1.94 1.38 EnvSt… 1.94 1.38 1.41 -#> 2 Logistic 50 -8.65 5.85 1.94 1.38 EnvSt… 1.94 1.39 1.39 -#> 3 Logistic 50 -8.65 5.85 1.94 1.38 EnvSt… 1.94 1.49 1.30 +#> 1 Logistic 50 -4.86 7.54 1.99 1.42 EnvSt… 1.99 1.42 1.40 +#> 2 Logistic 50 -4.86 7.54 1.99 1.42 EnvSt… 1.99 1.44 1.38 +#> 3 Logistic 50 -4.86 7.54 1.99 1.42 EnvSt… 1.99 1.59 1.25 #> # … with abbreviated variable names ¹​location, ²​shape_ratio diff --git a/docs/reference/util_logistic_stats_tbl.html b/docs/reference/util_logistic_stats_tbl.html index 247b0505..708b6fff 100644 --- a/docs/reference/util_logistic_stats_tbl.html +++ b/docs/reference/util_logistic_stats_tbl.html @@ -133,10 +133,10 @@

Examples#> $ coeff_var <dbl> 3.289868 #> $ skewness <dbl> 0 #> $ kurtosis <dbl> 1.2 -#> $ computed_std_skew <dbl> 0.1404616 -#> $ computed_std_kurt <dbl> 2.854101 -#> $ ci_lo <dbl> -4.024896 -#> $ ci_hi <dbl> 3.746533 +#> $ computed_std_skew <dbl> 0.3656847 +#> $ computed_std_kurt <dbl> 2.531143 +#> $ ci_lo <dbl> -1.871882 +#> $ ci_hi <dbl> 2.833328 diff --git a/docs/reference/util_lognormal_param_estimate-1.png b/docs/reference/util_lognormal_param_estimate-1.png index 28f8a07d..1ab4100b 100644 Binary files a/docs/reference/util_lognormal_param_estimate-1.png and b/docs/reference/util_lognormal_param_estimate-1.png differ diff --git a/docs/reference/util_lognormal_param_estimate.html b/docs/reference/util_lognormal_param_estimate.html index b4931048..ff1308dc 100644 --- a/docs/reference/util_lognormal_param_estimate.html +++ b/docs/reference/util_lognormal_param_estimate.html @@ -158,8 +158,8 @@

Examples#> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Lognormal 50 1.42 75.8 EnvStats_MVUE 2.36 0.974 2.42 -#> 2 Lognormal 50 1.42 75.8 EnvStats_MME 2.36 0.964 2.45 +#> 1 Lognormal 50 1.59 112. EnvStats_MVUE 2.42 0.898 2.70 +#> 2 Lognormal 50 1.59 112. EnvStats_MME 2.42 0.889 2.73 diff --git a/docs/reference/util_lognormal_stats_tbl.html b/docs/reference/util_lognormal_stats_tbl.html index d5c6bd0b..d86d5865 100644 --- a/docs/reference/util_lognormal_stats_tbl.html +++ b/docs/reference/util_lognormal_stats_tbl.html @@ -133,10 +133,10 @@

Examples#> $ coeff_var <dbl> 1.310832 #> $ skewness <dbl> 6.184877 #> $ kurtosis <dbl> 113.9364 -#> $ computed_std_skew <dbl> 1.964519 -#> $ computed_std_kurt <dbl> 7.102225 -#> $ ci_lo <dbl> 0.2020056 -#> $ ci_hi <dbl> 5.006112 +#> $ computed_std_skew <dbl> 1.464458 +#> $ computed_std_kurt <dbl> 4.975176 +#> $ ci_lo <dbl> 0.1740245 +#> $ ci_hi <dbl> 3.078619 diff --git a/docs/reference/util_negative_binomial_param_estimate-1.png b/docs/reference/util_negative_binomial_param_estimate-1.png index 679d7ba2..d84ec6bb 100644 Binary files a/docs/reference/util_negative_binomial_param_estimate-1.png and b/docs/reference/util_negative_binomial_param_estimate-1.png differ diff --git a/docs/reference/util_negative_binomial_param_estimate.html b/docs/reference/util_negative_binomial_param_estimate.html index 2a00d3c0..d0fd993d 100644 --- a/docs/reference/util_negative_binomial_param_estimate.html +++ b/docs/reference/util_negative_binomial_param_estimate.html @@ -165,10 +165,10 @@

Examplest <- rnbinom(50, 1, .1) util_negative_binomial_param_estimate(t, .size = 1)$parameter_tbl #> # A tibble: 2 × 9 -#> dist_type samp_size min max mean method size prob shape…¹ -#> <chr> <int> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Negative Binomial 50 0 30 7.76 EnvStats_MM… 50 0.114 438 -#> 2 Negative Binomial 50 0 30 7.76 EnvStats_MM… 50 0.112 446. +#> dist_type samp_size min max mean method size prob shape…¹ +#> <chr> <int> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> +#> 1 Negative Binomial 50 0 56 12.6 EnvStats_M… 50 0.0734 681 +#> 2 Negative Binomial 50 0 56 12.6 EnvStats_M… 50 0.0721 694. #> # … with abbreviated variable name ¹​shape_ratio diff --git a/docs/reference/util_negative_binomial_stats_tbl.html b/docs/reference/util_negative_binomial_stats_tbl.html index 58a2bd58..93a4f58c 100644 --- a/docs/reference/util_negative_binomial_stats_tbl.html +++ b/docs/reference/util_negative_binomial_stats_tbl.html @@ -129,10 +129,10 @@

Examples#> $ coeff_var <dbl> 0.1234568 #> $ skewness <dbl> 3.478505 #> $ kurtosis <dbl> 14.1 -#> $ computed_std_skew <dbl> 1.601684 -#> $ computed_std_kurt <dbl> 5.293525 +#> $ computed_std_skew <dbl> 1.164844 +#> $ computed_std_kurt <dbl> 4.061276 #> $ ci_lo <dbl> 0 -#> $ ci_hi <dbl> 50.3 +#> $ ci_hi <dbl> 31.55 diff --git a/docs/reference/util_normal_param_estimate-1.png b/docs/reference/util_normal_param_estimate-1.png index 8f92d477..a5ea93b4 100644 Binary files a/docs/reference/util_normal_param_estimate-1.png and b/docs/reference/util_normal_param_estimate-1.png differ diff --git a/docs/reference/util_normal_param_estimate.html b/docs/reference/util_normal_param_estimate.html index 34be4003..cb4af75d 100644 --- a/docs/reference/util_normal_param_estimate.html +++ b/docs/reference/util_normal_param_estimate.html @@ -159,8 +159,8 @@

Examples#> # A tibble: 2 × 8 #> dist_type samp_size min max method mu stan_dev shape_ratio #> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Gaussian 50 -1.75 3.49 EnvStats_MME_MLE 0.236 0.993 0.237 -#> 2 Gaussian 50 -1.75 3.49 EnvStats_MVUE 0.236 1.00 0.235 +#> 1 Gaussian 50 -2.62 2.63 EnvStats_MME_MLE 0.162 1.12 0.146 +#> 2 Gaussian 50 -2.62 2.63 EnvStats_MVUE 0.162 1.13 0.144 diff --git a/docs/reference/util_normal_stats_tbl.html b/docs/reference/util_normal_stats_tbl.html index 475d4d0c..a8baa778 100644 --- a/docs/reference/util_normal_stats_tbl.html +++ b/docs/reference/util_normal_stats_tbl.html @@ -127,16 +127,16 @@

Examples#> $ points <dbl> 50 #> $ simulations <dbl> 1 #> $ mean <dbl> 0 -#> $ median <dbl> -0.1279899 +#> $ median <dbl> -0.1220474 #> $ mode <dbl> 0 #> $ std_dv <dbl> 1 #> $ coeff_var <dbl> Inf #> $ skewness <dbl> 0 #> $ kurtosis <dbl> 3 -#> $ computed_std_skew <dbl> 0.3535038 -#> $ computed_std_kurt <dbl> 2.3906 -#> $ ci_lo <dbl> -1.587755 -#> $ ci_hi <dbl> 1.990075 +#> $ computed_std_skew <dbl> -0.02719793 +#> $ computed_std_kurt <dbl> 2.264517 +#> $ ci_lo <dbl> -1.63738 +#> $ ci_hi <dbl> 1.30215 diff --git a/docs/reference/util_pareto_param_estimate-1.png b/docs/reference/util_pareto_param_estimate-1.png index 5bf56070..e71a58f8 100644 Binary files a/docs/reference/util_pareto_param_estimate-1.png and b/docs/reference/util_pareto_param_estimate-1.png differ diff --git a/docs/reference/util_pareto_param_estimate.html b/docs/reference/util_pareto_param_estimate.html index faa37fbf..74122d51 100644 --- a/docs/reference/util_pareto_param_estimate.html +++ b/docs/reference/util_pareto_param_estimate.html @@ -159,10 +159,10 @@

Examplest <- tidy_pareto(50, 1, 1) %>% pull(y) util_pareto_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 -#> dist_type samp_size min max method shape scale shape_ratio -#> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Pareto 50 0.00682 66.5 LSE 0.146 0.496 0.295 -#> 2 Pareto 50 0.00682 66.5 MLE 0.00682 0.198 0.0344 +#> dist_type samp_size min max method shape scale shape_ratio +#> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> +#> 1 Pareto 50 0.0296 32.8 LSE 0.146 0.497 0.293 +#> 2 Pareto 50 0.0296 32.8 MLE 0.0296 0.280 0.106 diff --git a/docs/reference/util_pareto_stats_tbl.html b/docs/reference/util_pareto_stats_tbl.html index 8b5734e3..b5630eca 100644 --- a/docs/reference/util_pareto_stats_tbl.html +++ b/docs/reference/util_pareto_stats_tbl.html @@ -135,10 +135,10 @@

Examples#> $ coeff_var <dbl> 0.000154321 #> $ skewness <dbl> 2.811057 #> $ kurtosis <dbl> 14.82857 -#> $ computed_std_skew <dbl> 1.753089 -#> $ computed_std_kurt <dbl> 5.826765 -#> $ ci_lo <dbl> 0.0004801316 -#> $ ci_hi <dbl> 0.03972543 +#> $ computed_std_skew <dbl> 1.242909 +#> $ computed_std_kurt <dbl> 3.929721 +#> $ ci_lo <dbl> 0.0002854128 +#> $ ci_hi <dbl> 0.03200106 diff --git a/docs/reference/util_poisson_param_estimate-1.png b/docs/reference/util_poisson_param_estimate-1.png index a5e632b2..5e3ca130 100644 Binary files a/docs/reference/util_poisson_param_estimate-1.png and b/docs/reference/util_poisson_param_estimate-1.png differ diff --git a/docs/reference/util_poisson_param_estimate.html b/docs/reference/util_poisson_param_estimate.html index 82e295b4..021220bb 100644 --- a/docs/reference/util_poisson_param_estimate.html +++ b/docs/reference/util_poisson_param_estimate.html @@ -146,7 +146,7 @@

Examples#> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> <chr> <int> <dbl> <dbl> <chr> <dbl> -#> 1 Posson 50 1 12 MLE 4.78 +#> 1 Posson 50 1 14 MLE 5.46 diff --git a/docs/reference/util_poisson_stats_tbl.html b/docs/reference/util_poisson_stats_tbl.html index 44609045..84e4ff24 100644 --- a/docs/reference/util_poisson_stats_tbl.html +++ b/docs/reference/util_poisson_stats_tbl.html @@ -133,8 +133,8 @@

Examples#> $ coeff_var <dbl> 1 #> $ skewness <dbl> 1 #> $ kurtosis <dbl> 4 -#> $ computed_std_skew <dbl> 0.5824453 -#> $ computed_std_kurt <dbl> 2.221336 +#> $ computed_std_skew <dbl> 0.9220841 +#> $ computed_std_kurt <dbl> 3.30817 #> $ ci_lo <dbl> 0 #> $ ci_hi <dbl> 3 diff --git a/docs/reference/util_t_stats_tbl.html b/docs/reference/util_t_stats_tbl.html index 866d342c..bdc40d5d 100644 --- a/docs/reference/util_t_stats_tbl.html +++ b/docs/reference/util_t_stats_tbl.html @@ -131,10 +131,10 @@

Examples#> $ coeff_var <chr> "undefined" #> $ skewness <dbl> 0 #> $ kurtosis <chr> "undefined" -#> $ computed_std_skew <dbl> -4.277852 -#> $ computed_std_kurt <dbl> 25.33079 -#> $ ci_lo <dbl> -8.982581 -#> $ ci_hi <dbl> 3.328438 +#> $ computed_std_skew <dbl> -1.587054 +#> $ computed_std_kurt <dbl> 9.068707 +#> $ ci_lo <dbl> -8.367309 +#> $ ci_hi <dbl> 7.548309 diff --git a/docs/reference/util_uniform_param_estimate-1.png b/docs/reference/util_uniform_param_estimate-1.png index 03e89717..a6a2d8a2 100644 Binary files a/docs/reference/util_uniform_param_estimate-1.png and b/docs/reference/util_uniform_param_estimate-1.png differ diff --git a/docs/reference/util_uniform_param_estimate.html b/docs/reference/util_uniform_param_estimate.html index 2821212a..7890cf0c 100644 --- a/docs/reference/util_uniform_param_estimate.html +++ b/docs/reference/util_uniform_param_estimate.html @@ -134,8 +134,8 @@

Examples#> # A tibble: 2 × 8 #> dist_type samp_size min max method min_est max_est ratio #> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Uniform 50 1.06 2.93 NIST_MME 1.01 2.89 0.351 -#> 2 Uniform 50 1.06 2.93 NIST_MLE 1 3 0.333 +#> 1 Uniform 50 1.00 3.00 NIST_MME 1.09 3.09 0.354 +#> 2 Uniform 50 1.00 3.00 NIST_MLE 1 3 0.333 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_uniform_stats_tbl.html b/docs/reference/util_uniform_stats_tbl.html index 9f6684ca..26f240cc 100644 --- a/docs/reference/util_uniform_stats_tbl.html +++ b/docs/reference/util_uniform_stats_tbl.html @@ -131,10 +131,10 @@

Examples#> $ coeff_var <dbl> 0.5773503 #> $ skewness <dbl> 0 #> $ kurtosis <dbl> 1.8 -#> $ computed_std_skew <dbl> -0.1081732 -#> $ computed_std_kurt <dbl> 1.875426 -#> $ ci_lo <dbl> 0.05778033 -#> $ ci_hi <dbl> 0.9367315 +#> $ computed_std_skew <dbl> 0.05112003 +#> $ computed_std_kurt <dbl> 1.603629 +#> $ ci_lo <dbl> 0.01375033 +#> $ ci_hi <dbl> 0.939009 diff --git a/docs/reference/util_weibull_param_estimate-1.png b/docs/reference/util_weibull_param_estimate-1.png index f3be2e7a..1b64598a 100644 Binary files a/docs/reference/util_weibull_param_estimate-1.png and b/docs/reference/util_weibull_param_estimate-1.png differ diff --git a/docs/reference/util_weibull_param_estimate.html b/docs/reference/util_weibull_param_estimate.html index 04b0fb29..850436e5 100644 --- a/docs/reference/util_weibull_param_estimate.html +++ b/docs/reference/util_weibull_param_estimate.html @@ -135,7 +135,7 @@

Examples#> # A tibble: 1 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Weibull 50 0.0135 6.80 NIST 1.28 2.27 0.564 +#> 1 Weibull 50 0.0206 9.67 NIST 0.937 2.14 0.437 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_weibull_stats_tbl.html b/docs/reference/util_weibull_stats_tbl.html index 84562699..0f99e782 100644 --- a/docs/reference/util_weibull_stats_tbl.html +++ b/docs/reference/util_weibull_stats_tbl.html @@ -126,16 +126,16 @@

Examples#> $ distribution_type <chr> "continuous" #> $ points <dbl> 50 #> $ simulations <dbl> 1 -#> $ mean <dbl> 0.8890894 -#> $ median <dbl> 0.5468908 +#> $ mean <dbl> 0.7684299 +#> $ median <dbl> 0.5917829 #> $ mode <dbl> 0 #> $ range <chr> "0 to Inf" -#> $ std_dv <dbl> 0.961554 -#> $ coeff_var <dbl> 0.924586 -#> $ computed_std_skew <dbl> 0.8608088 -#> $ computed_std_kurt <dbl> 2.676956 -#> $ ci_lo <dbl> 0.04976536 -#> $ ci_hi <dbl> 2.665091 +#> $ std_dv <dbl> 0.8937609 +#> $ coeff_var <dbl> 0.7988085 +#> $ computed_std_skew <dbl> 1.053184 +#> $ computed_std_kurt <dbl> 3.430189 +#> $ ci_lo <dbl> 0.006940537 +#> $ ci_hi <dbl> 2.409566 diff --git a/docs/search.json b/docs/search.json index 7f73e68a..2473e64b 100644 --- a/docs/search.json +++ b/docs/search.json @@ -1 +1 @@ -[{"path":"https://www.spsanderson.com/TidyDensity/articles/getting-started.html","id":"example","dir":"Articles","previous_headings":"","what":"Example","title":"Getting Started with TidyDensity","text":"basic example shows easy generate data TidyDensity: example plot tidy_normal data. can also take look plots number simulations greater nine. automatically turn legend become noisy.","code":"library(TidyDensity) library(dplyr) library(ggplot2) tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.60 -3.66 0.000227 0.5 1.58 #> 2 1 2 0.985 -3.52 0.000602 0.508 0.841 #> 3 1 3 0.644 -3.39 0.00142 0.516 0.586 #> 4 1 4 1.20 -3.25 0.00298 0.524 1.03 #> 5 1 5 -0.0886 -3.11 0.00555 0.533 0.129 #> 6 1 6 -0.0347 -2.98 0.00926 0.541 0.161 #> 7 1 7 1.28 -2.84 0.0139 0.549 1.11 #> 8 1 8 1.14 -2.70 0.0191 0.557 0.980 #> 9 1 9 0.0559 -2.57 0.0246 0.565 0.214 #> 10 1 10 -2.47 -2.43 0.0309 0.573 -Inf #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows tn <- tidy_normal(.n = 100, .num_sims = 6) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\") tn <- tidy_normal(.n = 100, .num_sims = 20) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Steven Sanderson. Author, maintainer. Steven Sanderson. Copyright holder.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Sanderson S (2022). TidyDensity: Functions Tidy Analysis Generation Random Data. R package version 1.2.0.9000, https://github.com/spsanderson/TidyDensity.","code":"@Manual{, title = {TidyDensity: Functions for Tidy Analysis and Generation of Random Data}, author = {Steven Sanderson}, year = {2022}, note = {R package version 1.2.0.9000}, url = {https://github.com/spsanderson/TidyDensity}, }"},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement spsanderson@gmail.com. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.0, available https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"tidydensity-","dir":"","previous_headings":"","what":"Functions for Tidy Analysis and Generation of Random Data","title":"Functions for Tidy Analysis and Generation of Random Data","text":"goal TidyDensity make working random numbers different distributions easy. tidy_ distribution functions provide following components: [r_] [d_] [q_] [p_]","code":""},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Functions for Tidy Analysis and Generation of Random Data","text":"can install released version TidyDensity CRAN : development version GitHub :","code":"install.packages(\"TidyDensity\") # install.packages(\"devtools\") devtools::install_github(\"spsanderson/TidyDensity\")"},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"example","dir":"","previous_headings":"","what":"Example","title":"Functions for Tidy Analysis and Generation of Random Data","text":"basic example shows solve common problem: example plot tidy_normal data. can also take look plots number simulations greater nine. automatically turn legend become noisy.","code":"library(TidyDensity) library(dplyr) library(ggplot2) tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.02 -3.45 0.000231 0.5 0.334 #> 2 1 2 0.807 -3.29 0.000697 0.508 0.229 #> 3 1 3 0.558 -3.14 0.00181 0.516 0.108 #> 4 1 4 -0.113 -2.98 0.00401 0.524 -0.216 #> 5 1 5 0.519 -2.83 0.00764 0.533 0.0890 #> 6 1 6 0.615 -2.68 0.0126 0.541 0.136 #> 7 1 7 -1.01 -2.52 0.0181 0.549 -0.698 #> 8 1 8 0.180 -2.37 0.0233 0.557 -0.0738 #> 9 1 9 0.0577 -2.21 0.0285 0.565 -0.133 #> 10 1 10 -1.09 -2.06 0.0354 0.573 -0.747 #> # … with 40 more rows tn <- tidy_normal(.n = 100, .num_sims = 6) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\") tn <- tidy_normal(.n = 100, .num_sims = 20) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2022 Steven Paul Sandeson II, MPH Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"Unnest data output tidy_bootstrap().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"","code":"bootstrap_unnest_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":".data data passed tidy_bootstrap() function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"function takes input output tidy_bootstrap() function returns two column tibble. columns sim_number y looks attribute comes using tidy_bootstrap() work unless data comes function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"","code":"tb <- tidy_bootstrap(.x = mtcars$mpg) bootstrap_unnest_tbl(tb) #> # A tibble: 50,000 × 2 #> sim_number y #> #> 1 1 13.3 #> 2 1 19.2 #> 3 1 19.2 #> 4 1 27.3 #> 5 1 10.4 #> 6 1 21 #> 7 1 15.5 #> 8 1 18.7 #> 9 1 15.2 #> 10 1 22.8 #> # … with 49,990 more rows #> # ℹ Use `print(n = ...)` to see more rows bootstrap_unnest_tbl(tb) %>% tidy_distribution_summary_tbl(sim_number) #> # A tibble: 2,000 × 13 #> sim_num…¹ mean_…² media…³ std_val min_val max_val skewn…⁴ kurto…⁵ range iqr #> #> 1 1 20.6 19.2 6.27 10.4 32.4 0.332 2.29 22 10.5 #> 2 2 18.1 17.8 5.74 10.4 32.4 0.773 3.39 22 5.8 #> 3 3 20.1 21 4.54 10.4 30.4 0.0588 3.07 20 3.7 #> 4 4 19.9 19.2 5.04 10.4 30.4 0.526 2.73 20 6.4 #> 5 5 20.1 18.7 6.20 10.4 30.4 0.317 1.80 20 11 #> 6 6 18.7 17.8 5.13 10.4 32.4 1.00 3.90 22 5.8 #> 7 7 21.6 19.7 8.09 10.4 33.9 0.534 1.74 23.5 15.7 #> 8 8 17.7 16.4 5.03 10.4 30.4 0.768 3.34 20 4.5 #> 9 9 18.2 19.2 4.45 10.4 27.3 -0.0667 2.62 16.9 5.8 #> 10 10 19.5 18.1 5.95 10.4 32.4 0.894 2.82 22 6 #> # … with 1,990 more rows, 3 more variables: variance , ci_low , #> # ci_high , and abbreviated variable names ¹​sim_number, ²​mean_val, #> # ³​median_val, ⁴​skewness, ⁵​kurtosis #> # ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":null,"dir":"Reference","previous_headings":"","what":"Confidence Interval Generic — ci_hi","title":"Confidence Interval Generic — ci_hi","text":"Gets upper 97.5% quantile numeric vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Confidence Interval Generic — ci_hi","text":"","code":"ci_hi(.x, .na_rm = FALSE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Confidence Interval Generic — ci_hi","text":".x vector numeric values .na_rm Boolean, defaults FALSE. Passed quantile function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Confidence Interval Generic — ci_hi","text":"numeric value.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Confidence Interval Generic — ci_hi","text":"Gets upper 97.5% quantile numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Confidence Interval Generic — ci_hi","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Confidence Interval Generic — ci_hi","text":"","code":"x <- mtcars$mpg ci_hi(x) #> [1] 32.7375"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":null,"dir":"Reference","previous_headings":"","what":"Confidence Interval Generic — ci_lo","title":"Confidence Interval Generic — ci_lo","text":"Gets lower 2.5% quantile numeric vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Confidence Interval Generic — ci_lo","text":"","code":"ci_lo(.x, .na_rm = FALSE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Confidence Interval Generic — ci_lo","text":".x vector numeric values .na_rm Boolean, defaults FALSE. Passed quantile function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Confidence Interval Generic — ci_lo","text":"numeric value.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Confidence Interval Generic — ci_lo","text":"Gets lower 2.5% quantile numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Confidence Interval Generic — ci_lo","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Confidence Interval Generic — ci_lo","text":"","code":"x <- mtcars$mpg ci_lo(x) #> [1] 10.4"},{"path":"https://www.spsanderson.com/TidyDensity/reference/color_blind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — color_blind","title":"Provide Colorblind Compliant Colors — color_blind","text":"8 Hex RGB color definitions suitable charts colorblind people.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/color_blind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — color_blind","text":"","code":"color_blind()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"Provide Colorblind Compliant Colors","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"","code":"td_scale_color_colorblind(..., theme = \"td\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"... Data passed function theme defaults td allowed value","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"Provide Colorblind Compliant Colors","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"","code":"td_scale_fill_colorblind(..., theme = \"td\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"... Data passed function theme defaults td allowed value","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidyeval.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy eval helpers — tidyeval","title":"Tidy eval helpers — tidyeval","text":"page lists tidy eval tools reexported package rlang. learn using tidy eval scripts packages high level, see dplyr programming vignette ggplot2 packages vignette. Metaprogramming section Advanced R may also useful deeper dive. tidy eval operators {{, !!, !!! syntactic constructs specially interpreted tidy eval functions. mostly need {{, !! !!! advanced operators use simple cases. curly-curly operator {{ allows tunnel data-variables passed function arguments inside tidy eval functions. {{ designed individual arguments. pass multiple arguments contained dots, use ... normal way. enquo() enquos() delay execution one several function arguments. former returns single expression, latter returns list expressions. defused, expressions longer evaluate . must injected back evaluation context !! (single expression) !!! (list expressions). simple case, code equivalent usage {{ ... . Defusing enquo() enquos() needed complex cases, instance need inspect modify expressions way. .data pronoun object represents current slice data. variable name string, use .data pronoun subset variable [[. Another tidy eval operator :=. makes possible use glue curly-curly syntax LHS =. technical reasons, R language support complex expressions left =, use := workaround. Many tidy eval functions like dplyr::mutate() dplyr::summarise() give automatic name unnamed inputs. need create sort automatic names , use as_label(). instance, glue-tunnelling syntax can reproduced manually : Expressions defused enquo() (tunnelled {{) need simple column names, can arbitrarily complex. as_label() handles cases gracefully. code assumes simple column name, use as_name() instead. safer throws error input name expected.","code":"my_function <- function(data, var, ...) { data %>% group_by(...) %>% summarise(mean = mean({{ var }})) } my_function <- function(data, var, ...) { # Defuse var <- enquo(var) dots <- enquos(...) # Inject data %>% group_by(!!!dots) %>% summarise(mean = mean(!!var)) } my_var <- \"disp\" mtcars %>% summarise(mean = mean(.data[[my_var]])) my_function <- function(data, var, suffix = \"foo\") { # Use `{{` to tunnel function arguments and the usual glue # operator `{` to interpolate plain strings. data %>% summarise(\"{{ var }}_mean_{suffix}\" := mean({{ var }})) } my_function <- function(data, var, suffix = \"foo\") { var <- enquo(var) prefix <- as_label(var) data %>% summarise(\"{prefix}_mean_{suffix}\" := mean(!!var)) }"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Density Data — tidy_autoplot","title":"Automatic Plot of Density Data — tidy_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq mcmc number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Density Data — tidy_autoplot","text":"","code":"tidy_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Density Data — tidy_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Density Data — tidy_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Density Data — tidy_autoplot","text":"function spit one following plots: density quantile probability qq mcmc","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Density Data — tidy_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Density Data — tidy_autoplot","text":"","code":"tidy_normal(.num_sims = 5) %>% tidy_autoplot() tidy_normal(.num_sims = 20) %>% tidy_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"function generate n random points beta distribution user provided, .shape1, .shape2, .ncp non-centrality parameter, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"","code":"tidy_beta(.n = 50, .shape1 = 1, .shape2 = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":".n number randomly generated points want. .shape1 non-negative parameter Beta distribution. .shape2 non-negative parameter Beta distribution. .ncp non-centrality parameter Beta distribution. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"function uses underlying stats::rbeta(), underlying p, d, q functions. information please see stats::rbeta()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"","code":"tidy_beta() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.612 -0.321 0.00317 0 0.591 #> 2 1 2 0.0917 -0.286 0.00743 0.0204 0.0363 #> 3 1 3 0.943 -0.252 0.0163 0.0408 0.945 #> 4 1 4 0.126 -0.217 0.0331 0.0612 0.0733 #> 5 1 5 0.197 -0.182 0.0631 0.0816 0.149 #> 6 1 6 0.101 -0.148 0.112 0.102 0.0463 #> 7 1 7 0.261 -0.113 0.186 0.122 0.217 #> 8 1 8 0.952 -0.0788 0.289 0.143 0.955 #> 9 1 9 0.699 -0.0442 0.420 0.163 0.684 #> 10 1 10 0.575 -0.00961 0.574 0.184 0.552 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"function generate n random points binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"","code":"tidy_binomial(.n = 50, .size = 0, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"function uses underlying stats::rbinom(), underlying p, d, q functions. information please see stats::rbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"","code":"tidy_binomial() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":null,"dir":"Reference","previous_headings":"","what":"Bootstrap Empirical Data — tidy_bootstrap","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"Takes input vector numeric data produces bootstrapped nested tibble simulation number.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"","code":"tidy_bootstrap( .x, .num_sims = 2000, .proportion = 0.8, .distribution_type = \"continuous\" )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bootstrap Empirical Data — tidy_bootstrap","text":".x vector data passed function. Must numeric vector. .num_sims default 2000, can set anything desired. warning pass console value less 2000. .proportion much original data want pass sampling function. default 0.80 (80%) .distribution_type can either 'continuous' 'discrete'","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"nested tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"function take numeric input vector produce tibble bootstrapped values list. table output two columns: sim_number bootstrap_samples sim_number corresponds many times want data resampled, bootstrap_samples column contains list boostrapped resampled data.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) #> # A tibble: 2,000 × 2 #> sim_number bootstrap_samples #> #> 1 1 #> 2 2 #> 3 3 #> 4 4 #> 5 5 #> 6 6 #> 7 7 #> 8 8 #> 9 9 #> 10 10 #> # … with 1,990 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"function generate n random points Burr distribution user provided, .shape1, .shape2, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"","code":"tidy_burr( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":".n number randomly generated points want. .shape1 Must strictly positive. .shape2 Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"function uses underlying actuar::rburr(), underlying p, d, q functions. information please see actuar::rburr()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"","code":"tidy_burr() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.50 -1.48 0.00166 0 0.0202 #> 2 1 2 0.316 0.129 0.389 0.0200 0.00415 #> 3 1 3 1.93 1.74 0.158 0.0392 0.0261 #> 4 1 4 0.590 3.35 0.0293 0.0577 0.00781 #> 5 1 5 0.0130 4.95 0.0140 0.0755 0.000133 #> 6 1 6 0.265 6.56 0.0220 0.0926 0.00347 #> 7 1 7 1.55 8.17 0.000112 0.109 0.0208 #> 8 1 8 0.0489 9.78 0.00161 0.125 0.000607 #> 9 1 9 1.09 11.4 0.0225 0.140 0.0146 #> 10 1 10 0.431 13.0 0.000564 0.155 0.00568 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"function generate n random points cauchy distribution user provided, .location, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"","code":"tidy_cauchy(.n = 50, .location = 0, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":".n number randomly generated points want. .location location parameter. .scale scale parameter, must greater equal 0. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"function uses underlying stats::rcauchy(), underlying p, d, q functions. information please see stats::rcauchy()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"","code":"tidy_cauchy() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.464 -216. 2.15e- 4 0.5 11.4 #> 2 1 2 -0.154 -211. 1.11e- 4 0.506 10.3 #> 3 1 3 0.107 -207. 0 0.513 10.8 #> 4 1 4 1.55 -202. 4.31e-18 0.519 13.9 #> 5 1 5 -2.28 -197. 1.55e-18 0.526 7.85 #> 6 1 6 -0.376 -193. 1.53e-19 0.532 10.0 #> 7 1 7 1.97 -188. 0 0.539 15.1 #> 8 1 8 -2.02 -184. 2.12e-18 0.545 8.09 #> 9 1 9 0.111 -179. 1.82e-18 0.552 10.8 #> 10 1 10 -3.03 -174. 4.87e-18 0.558 7.23 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"function generate n random points chisquare distribution user provided, .df, .ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"","code":"tidy_chisquare(.n = 50, .df = 1, .ncp = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":".n number randomly generated points want. .df Degrees freedom (non-negative can non-integer) .ncp Non-centrality parameter, must non-negative. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"function uses underlying stats::rchisq(), underlying p, d, q functions. information please see stats::rchisq()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"","code":"tidy_chisquare() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.00 -2.54 0.000994 0 0.0554 #> 2 1 2 1.32 -2.26 0.00267 0.0691 0.0958 #> 3 1 3 0.587 -1.98 0.00645 0.0978 0.0190 #> 4 1 4 1.53 -1.69 0.0140 0.120 0.129 #> 5 1 5 0.425 -1.41 0.0275 0.138 0.00997 #> 6 1 6 0.0229 -1.13 0.0488 0.155 0.0000288 #> 7 1 7 1.39 -0.843 0.0785 0.169 0.106 #> 8 1 8 2.44 -0.559 0.115 0.183 0.328 #> 9 1 9 0.685 -0.276 0.154 0.195 0.0259 #> 10 1 10 1.90 0.00723 0.191 0.207 0.199 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"","code":"tidy_combined_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":".data data passed function tidy_multi_dist() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"","code":"combined_tbl <- tidy_combine_distributions( tidy_normal(), tidy_gamma(), tidy_beta() ) combined_tbl #> # A tibble: 150 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 1.19 -3.78 0.000213 0.5 0.925 Gaussian c(0, 1) #> 2 1 2 1.99 -3.64 0.000558 0.508 Inf Gaussian c(0, 1) #> 3 1 3 0.433 -3.49 0.00131 0.516 0.396 Gaussian c(0, 1) #> 4 1 4 1.24 -3.35 0.00274 0.524 0.966 Gaussian c(0, 1) #> 5 1 5 -0.192 -3.21 0.00516 0.533 0.0378 Gaussian c(0, 1) #> 6 1 6 -0.369 -3.06 0.00878 0.541 -0.0606 Gaussian c(0, 1) #> 7 1 7 0.305 -2.92 0.0136 0.549 0.320 Gaussian c(0, 1) #> 8 1 8 -0.632 -2.78 0.0195 0.557 -0.209 Gaussian c(0, 1) #> 9 1 9 -1.91 -2.63 0.0263 0.565 -1.11 Gaussian c(0, 1) #> 10 1 10 -0.379 -2.49 0.0342 0.573 -0.0663 Gaussian c(0, 1) #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows combined_tbl %>% tidy_combined_autoplot() combined_tbl %>% tidy_combined_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":null,"dir":"Reference","previous_headings":"","what":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"allows user specify n number tidy_ distributions can combined single tibble. preferred method combining multiple distributions different types, example Gaussian distribution Beta distribution. generates single tibble added column dist_type give distribution family name associated parameters.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"","code":"tidy_combine_distributions(...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"... ... can place different distributions","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"Allows user generate tibble different tidy_ distributions","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"","code":"tn <- tidy_normal() tb <- tidy_beta() tc <- tidy_cauchy() tidy_combine_distributions(tn, tb, tc) #> # A tibble: 150 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 -0.856 -2.84 0.000309 0.5 -0.648 Gaussian c(0, 1) #> 2 1 2 -1.78 -2.73 0.000815 0.508 -Inf Gaussian c(0, 1) #> 3 1 3 -0.501 -2.61 0.00195 0.516 -0.364 Gaussian c(0, 1) #> 4 1 4 -0.348 -2.49 0.00423 0.524 -0.251 Gaussian c(0, 1) #> 5 1 5 0.616 -2.38 0.00836 0.533 0.443 Gaussian c(0, 1) #> 6 1 6 0.308 -2.26 0.0151 0.541 0.215 Gaussian c(0, 1) #> 7 1 7 0.576 -2.15 0.0248 0.549 0.413 Gaussian c(0, 1) #> 8 1 8 -0.115 -2.03 0.0377 0.557 -0.0849 Gaussian c(0, 1) #> 9 1 9 -0.489 -1.91 0.0531 0.565 -0.355 Gaussian c(0, 1) #> 10 1 10 -0.377 -1.80 0.0703 0.573 -0.272 Gaussian c(0, 1) #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows ## OR tidy_combine_distributions( tidy_normal(), tidy_beta(), tidy_cauchy(), tidy_logistic() ) #> # A tibble: 200 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 -0.731 -3.67 0.000250 0.5 -0.308 Gaussian c(0, 1) #> 2 1 2 -0.475 -3.53 0.000752 0.508 -0.171 Gaussian c(0, 1) #> 3 1 3 -1.85 -3.38 0.00196 0.516 -1.05 Gaussian c(0, 1) #> 4 1 4 -0.0244 -3.24 0.00445 0.524 0.0628 Gaussian c(0, 1) #> 5 1 5 -1.48 -3.10 0.00879 0.533 -0.759 Gaussian c(0, 1) #> 6 1 6 0.708 -2.95 0.0153 0.541 0.458 Gaussian c(0, 1) #> 7 1 7 1.96 -2.81 0.0238 0.549 1.51 Gaussian c(0, 1) #> 8 1 8 1.03 -2.66 0.0334 0.557 0.651 Gaussian c(0, 1) #> 9 1 9 0.219 -2.52 0.0434 0.565 0.190 Gaussian c(0, 1) #> 10 1 10 0.203 -2.38 0.0535 0.573 0.182 Gaussian c(0, 1) #> # … with 190 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Compare Empirical Data to Distributions — tidy_distribution_comparison","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"Compare empirical data set different distributions help find distribution best fit.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"","code":"tidy_distribution_comparison(.x, .distribution_type = \"continuous\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":".x data set passed function .distribution_type kind data , can one continuous discrete","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"invisible list object. tibble printed.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"purpose function take data set provided try find distribution may fit best. parameter .distribution_type must set either continuous discrete order function try appropriate types distributions. following distributions used: Continuous: tidy_beta tidy_cauchy tidy_exponential tidy_gamma tidy_logistic tidy_lognormal tidy_pareto tidy_uniform tidy_weibull Discrete: tidy_binomial tidy_geometric tidy_hypergeometric tidy_poisson","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"","code":"xc <- mtcars$mpg tidy_distribution_comparison(xc, \"continuous\") #> For the beta distribution, its mean 'mu' should be 0 < mu < 1. The data will #> therefore be scaled to enforce this. #> # A tibble: 9 × 2 #> dist_with_params abs_tot_deviance #> #> 1 Lognormal c(2.96, 0.29) 1.57 #> 2 Gamma c(11.47, 1.75) 1.92 #> 3 Beta c(1.11, 1.58, 0) 2.27 #> 4 Weibull c(3.58, 22.29) 2.79 #> 5 Pareto c(10.4, 1.62) 2.83 #> 6 Uniform c(8.34, 31.84) 3.77 #> 7 Logistic c(20.09, 3.27) 4.47 #> 8 Exponential c(0.05) 6.55 #> 9 Cauchy c(19.2, 7.38) 10.6 xd <- trunc(xc) tidy_distribution_comparison(xd, \"discrete\") #> # A tibble: 4 × 2 #> dist_with_params abs_tot_deviance #> #> 1 Hypergeometric c(21, 11, 21) 0.188 #> 2 Poisson c(19.69) 0.288 #> 3 Binomial c(32, 0.03) 3.81 #> 4 Geometric c(0.05) 5.82"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"function returns summary statistics tibble. use y column tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"","code":"tidy_distribution_summary_tbl(.data, ...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":".data data going passed tidy_ distribution function. ... grouping variable gets passed dplyr::group_by() dplyr::select().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"summary stats tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"function takes tidy_ distribution table return tibble following information: sim_number mean_val median_val std_val min_val max_val skewness kurtosis range iqr variance kurtosis skewness come package healthyR.ai","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"","code":"library(dplyr) #> #> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union tn <- tidy_normal(.num_sims = 5) tb <- tidy_beta(.num_sims = 5) tidy_distribution_summary_tbl(tn) #> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> #> 1 -0.00689 -0.0508 0.985 -2.62 2.48 -0.0740 2.66 5.09 1.42 0.970 #> # … with 2 more variables: ci_low , ci_high , and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance #> # ℹ Use `colnames()` to see all variable names tidy_distribution_summary_tbl(tn, sim_number) #> # A tibble: 5 × 13 #> sim_num…¹ mean_val media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> #> 1 1 -0.00930 0.0472 1.14 -2.62 2.23 -0.198 2.33 4.84 1.73 #> 2 2 0.0438 -0.0657 0.963 -2.04 2.36 0.196 2.94 4.39 1.22 #> 3 3 -0.207 -0.236 0.997 -2.59 1.74 -0.153 2.40 4.33 1.43 #> 4 4 0.273 0.213 0.971 -1.96 2.48 -0.0985 2.59 4.44 1.20 #> 5 5 -0.135 -0.122 0.793 -1.83 1.38 -0.199 2.34 3.21 1.21 #> # … with 3 more variables: variance , ci_low , ci_high , and #> # abbreviated variable names ¹​sim_number, ²​median_val, ³​skewness, ⁴​kurtosis #> # ℹ Use `colnames()` to see all variable names data_tbl <- tidy_combine_distributions(tn, tb) tidy_distribution_summary_tbl(data_tbl) #> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> #> 1 0.261 0.422 0.771 -2.62 2.48 -0.859 4.30 5.09 0.795 0.595 #> # … with 2 more variables: ci_low , ci_high , and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance #> # ℹ Use `colnames()` to see all variable names tidy_distribution_summary_tbl(data_tbl, dist_type) #> # A tibble: 2 × 13 #> dist_t…¹ mean_val media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> #> 1 Gaussia… -0.00689 -0.0508 0.985 -2.62e+0 2.48 -0.0740 2.66 5.09 1.42 #> 2 Beta c(… 0.529 0.526 0.279 2.34e-4 0.999 -0.0998 1.90 0.999 0.446 #> # … with 3 more variables: variance , ci_low , ci_high , and #> # abbreviated variable names ¹​dist_type, ²​median_val, ³​skewness, ⁴​kurtosis #> # ℹ Use `colnames()` to see all variable names"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Empirical — tidy_empirical","title":"Tidy Empirical — tidy_empirical","text":"function takes single argument .x vector return tibble information similar tidy_ distribution functions. y column set equal dy density function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Empirical — tidy_empirical","text":"","code":"tidy_empirical(.x, .num_sims = 1, .distribution_type = \"continuous\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Empirical — tidy_empirical","text":".x vector numbers .num_sims many simulations run, defaults 1. .distribution_type string either \"continuous\" \"discrete\". function default \"continuous\"","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Empirical — tidy_empirical","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Empirical — tidy_empirical","text":"function takes single argument .x vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Empirical — tidy_empirical","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Empirical — tidy_empirical","text":"","code":"x <- mtcars$mpg tidy_empirical(.x = x, .distribution_type = \"continuous\") #> # A tibble: 32 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 21 2.97 0.000114 0.625 10.4 #> 2 1 2 21 4.21 0.000455 0.625 10.4 #> 3 1 3 22.8 5.44 0.00142 0.781 13.3 #> 4 1 4 21.4 6.68 0.00355 0.688 14.3 #> 5 1 5 18.7 7.92 0.00721 0.469 14.7 #> 6 1 6 18.1 9.16 0.0124 0.438 15 #> 7 1 7 14.3 10.4 0.0192 0.125 15.2 #> 8 1 8 24.4 11.6 0.0281 0.812 15.2 #> 9 1 9 22.8 12.9 0.0395 0.781 15.5 #> 10 1 10 19.2 14.1 0.0516 0.531 15.8 #> # … with 22 more rows #> # ℹ Use `print(n = ...)` to see more rows tidy_empirical(.x = x, .num_sims = 10, .distribution_type = \"continuous\") #> # A tibble: 320 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 21.5 3.20 0.0000602 0.719 10.4 #> 2 1 2 19.7 4.42 0.000250 0.562 13.3 #> 3 1 3 14.3 5.64 0.000821 0.125 13.3 #> 4 1 4 19.7 6.87 0.00218 0.562 14.3 #> 5 1 5 33.9 8.09 0.00487 1 14.3 #> 6 1 6 22.8 9.31 0.00954 0.781 15.2 #> 7 1 7 24.4 10.5 0.0169 0.812 15.2 #> 8 1 8 14.3 11.8 0.0274 0.125 15.2 #> 9 1 9 15.2 13.0 0.0396 0.25 15.8 #> 10 1 10 18.7 14.2 0.0505 0.469 16.4 #> # … with 310 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"function generate n random points exponential distribution user provided, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"","code":"tidy_exponential(.n = 50, .rate = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":".n number randomly generated points want. .rate vector rates .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"function uses underlying stats::rexp(), underlying p, d, q functions. information please see stats::rexp()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"","code":"tidy_exponential() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.953 -0.603 0.00253 0 0.304 #> 2 1 2 0.956 -0.505 0.0101 0.0202 0.305 #> 3 1 3 1.02 -0.406 0.0322 0.0400 0.329 #> 4 1 4 0.233 -0.308 0.0833 0.0594 0.0636 #> 5 1 5 0.635 -0.210 0.176 0.0784 0.191 #> 6 1 6 0.938 -0.111 0.307 0.0970 0.299 #> 7 1 7 0.0366 -0.0131 0.455 0.115 0.00691 #> 8 1 8 0.506 0.0852 0.588 0.133 0.148 #> 9 1 9 0.333 0.183 0.683 0.151 0.0937 #> 10 1 10 2.16 0.282 0.733 0.168 0.915 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated F Distribution Tibble — tidy_f","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"function generate n random points rf distribution user provided, df1,df2, ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"","code":"tidy_f(.n = 50, .df1 = 1, .df2 = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":".n number randomly generated points want. .df1 Degrees freedom, Inf allowed. .df2 Degrees freedom, Inf allowed. .ncp Non-centrality parameter. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"function uses underlying stats::rf(), underlying p, d, q functions. information please see stats::rf()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"","code":"tidy_f() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.374 -4.63 1.92e- 2 0 8.35e- 8 #> 2 1 2 1.65 37.0 3.46e- 6 0.0903 1.62e- 6 #> 3 1 3 0.708 78.6 2.11e- 4 0.127 3.00e- 7 #> 4 1 4 26.2 120. 9.71e-20 0.154 4.09e- 4 #> 5 1 5 0.0273 162. 4.06e-23 0.177 4.41e-10 #> 6 1 6 14.5 204. 0 0.197 1.25e- 4 #> 7 1 7 1.05 245. 1.46e-19 0.214 6.57e- 7 #> 8 1 8 0.103 287. 0 0.230 6.38e- 9 #> 9 1 9 0.623 328. 4.04e-19 0.244 2.32e- 7 #> 10 1 10 0.145 370. 3.99e-20 0.258 1.26e- 8 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Density Data — tidy_four_autoplot","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"","code":"tidy_four_autoplot( .data, .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"","code":"tidy_normal(.num_sims = 5) %>% tidy_four_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"function generate n random points gamma distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"","code":"tidy_gamma(.n = 50, .shape = 1, .scale = 0.3, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":".n number randomly generated points want. .shape strictly 0 infinity. .scale standard deviation randomly generated data. strictly 0 infinity. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"function uses underlying stats::rgamma(), underlying p, d, q functions. information please see stats::rgamma()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"","code":"tidy_gamma() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.18 -0.318 0.00624 0 Inf #> 2 1 2 0.0931 -0.280 0.0177 0.0658 0.0238 #> 3 1 3 0.735 -0.243 0.0450 0.127 0.293 #> 4 1 4 0.123 -0.206 0.102 0.185 0.0321 #> 5 1 5 0.0557 -0.169 0.208 0.238 0.0137 #> 6 1 6 0.121 -0.132 0.380 0.288 0.0317 #> 7 1 7 0.0621 -0.0953 0.626 0.335 0.0154 #> 8 1 8 0.189 -0.0582 0.929 0.379 0.0518 #> 9 1 9 0.275 -0.0212 1.25 0.420 0.0790 #> 10 1 10 0.00619 0.0159 1.53 0.458 0.000687 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"function generate n random points generalized beta distribution user provided, .shape1, .shape2, .shape3, .rate, /.sclae, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"","code":"tidy_generalized_beta( .n = 50, .shape1 = 1, .shape2 = 1, .shape3 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":".n number randomly generated points want. .shape1 non-negative parameter Beta distribution. .shape2 non-negative parameter Beta distribution. .shape3 non-negative parameter Beta distribution. .rate alternative way specify .scale parameter. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"function uses underlying stats::rbeta(), underlying p, d, q functions. information please see stats::rbeta()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"","code":"tidy_generalized_beta() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.840 -0.398 0.00289 0 0.839 #> 2 1 2 0.383 -0.362 0.00658 0.0204 0.377 #> 3 1 3 0.584 -0.325 0.0140 0.0408 0.581 #> 4 1 4 0.964 -0.288 0.0277 0.0612 0.965 #> 5 1 5 0.0306 -0.251 0.0514 0.0816 0.0211 #> 6 1 6 0.117 -0.214 0.0894 0.102 0.109 #> 7 1 7 0.968 -0.177 0.146 0.122 0.968 #> 8 1 8 0.915 -0.140 0.222 0.143 0.915 #> 9 1 9 0.646 -0.104 0.319 0.163 0.643 #> 10 1 10 0.935 -0.0668 0.430 0.184 0.936 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"function generate n random points generalized Pareto distribution user provided, .shape1, .shape2, .rate .scale number #' random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"","code":"tidy_generalized_pareto( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":".n number randomly generated points want. .shape1 Must positive. .shape2 Must positive. .rate alternative way specify .scale argument .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"function uses underlying actuar::rgenpareto(), underlying p, d, q functions. information please see actuar::rgenpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"","code":"tidy_generalized_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.346 -1.48 1.82e- 3 0 0.00286 #> 2 1 2 5.12 0.864 3.71e- 1 0.02 0.0477 #> 3 1 3 1.62 3.21 2.86e- 2 0.0392 0.0145 #> 4 1 4 0.307 5.56 3.87e- 2 0.0577 0.00251 #> 5 1 5 0.0850 7.91 5.49e- 4 0.0755 0.000521 #> 6 1 6 1.28 10.3 3.75e-10 0.0926 0.0113 #> 7 1 7 4.44 12.6 6.56e- 3 0.109 0.0410 #> 8 1 8 0.353 15.0 7.15e- 5 0.125 0.00292 #> 9 1 9 0.0267 17.3 4.53e-16 0.140 0 #> 10 1 10 0.0598 19.6 0 0.155 0.000296 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"function generate n random points geometric distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"","code":"tidy_geometric(.n = 50, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":".n number randomly generated points want. .prob probability success trial 0 < prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"function uses underlying stats::rgeom(), underlying p, d, q functions. information please see stats::rgeom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"","code":"tidy_geometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"function generate n random points hypergeometric distribution user provided, m,nn, k, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"","code":"tidy_hypergeometric(.n = 50, .m = 0, .nn = 0, .k = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":".n number randomly generated points want. .m number white balls urn .nn number black balls urn .k number balls drawn fro urn. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"function uses underlying stats::rhyper(), underlying p, d, q functions. information please see stats::rhyper()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"","code":"tidy_hypergeometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"function generate n random points Inverse Burr distribution user provided, .shape1, .shape2, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"","code":"tidy_inverse_burr( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":".n number randomly generated points want. .shape1 Must strictly positive. .shape2 Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"function uses underlying actuar::rinvburr(), underlying p, d, q functions. information please see actuar::rinvburr()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"","code":"tidy_inverse_burr() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.657 -2.14 0.00140 0 0.00901 #> 2 1 2 0.685 -0.629 0.121 0.02 0.00941 #> 3 1 3 15.7 0.883 0.276 0.0392 0.289 #> 4 1 4 0.132 2.39 0.112 0.0577 0.00140 #> 5 1 5 0.418 3.91 0.0416 0.0755 0.00553 #> 6 1 6 6.32 5.42 0.00783 0.0926 0.0992 #> 7 1 7 3.70 6.93 0.0184 0.109 0.0555 #> 8 1 8 0.222 8.44 0.00272 0.125 0.00270 #> 9 1 9 1.41 9.95 0.0104 0.140 0.0201 #> 10 1 10 0.755 11.5 0.00235 0.155 0.0104 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"function generate n random points inverse exponential distribution user provided, .rate .scale number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"","code":"tidy_inverse_exponential(.n = 50, .rate = 1, .scale = 1/.rate, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":".n number randomly generated points want. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"function uses underlying actuar::rinvexp(), underlying p, d, q functions. information please see actuar::rinvexp()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"","code":"tidy_inverse_exponential() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.63 -3.20 0.000689 0 0.242 #> 2 1 2 0.704 -1.19 0.0487 5.24e-22 0.194 #> 3 1 3 9.10 0.813 0.197 2.29e-11 0.429 #> 4 1 4 0.570 2.82 0.105 8.06e- 8 0.184 #> 5 1 5 0.427 4.83 0.0727 4.79e- 6 0.170 #> 6 1 6 0.918 6.84 0.0260 5.55e- 5 0.208 #> 7 1 7 3.84 8.84 0.0149 2.84e- 4 0.311 #> 8 1 8 1.93 10.9 0.00507 9.12e- 4 0.253 #> 9 1 9 12.9 12.9 0.00709 2.19e- 3 0.507 #> 10 1 10 5.72 14.9 0.00166 4.32e- 3 0.357 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"function generate n random points inverse gamma distribution user provided, .shape, .rate, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"","code":"tidy_inverse_gamma( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"function uses underlying actuar::rinvgamma(), underlying p, d, q functions. information please see actuar::rinvgamma()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"","code":"tidy_inverse_gamma() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.392 -1.87 1.10e- 2 0 0.106 #> 2 1 2 4.84 16.4 1.45e- 4 5.24e-22 0.189 #> 3 1 3 3.22 34.7 0 2.29e-11 0.175 #> 4 1 4 0.972 53.0 0 8.06e- 8 0.139 #> 5 1 5 0.472 71.3 2.38e-15 4.79e- 6 0.115 #> 6 1 6 8.46 89.5 0 5.55e- 5 0.213 #> 7 1 7 0.498 108. 9.50e-19 2.84e- 4 0.118 #> 8 1 8 1.13 126. 0 9.12e- 4 0.143 #> 9 1 9 1.21 144. 8.60e-19 2.19e- 3 0.145 #> 10 1 10 0.461 163. 0 4.32e- 3 0.114 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"function generate n random points Inverse Gaussian distribution user provided, .mean, .shape, .dispersionThe function returns tibble simulation number column x column corresponds n randomly generated points. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"","code":"tidy_inverse_normal( .n = 50, .mean = 1, .shape = 1, .dispersion = 1/.shape, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":".n number randomly generated points want. .mean Must strictly positive. .shape Must strictly positive. .dispersion alternative way specify .shape. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"function uses underlying actuar::rinvgauss(). information please see rinvgauss()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"","code":"tidy_inverse_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.32 -0.763 0.00161 0 0.338 #> 2 1 2 1.58 -0.614 0.00623 6.89e-12 0.385 #> 3 1 3 1.42 -0.466 0.0199 1.98e- 6 0.356 #> 4 1 4 0.704 -0.318 0.0529 1.40e- 4 0.228 #> 5 1 5 0.248 -0.169 0.118 1.22e- 3 0.100 #> 6 1 6 0.846 -0.0210 0.220 4.54e- 3 0.254 #> 7 1 7 0.350 0.127 0.349 1.10e- 2 0.147 #> 8 1 8 0.426 0.276 0.473 2.09e- 2 0.169 #> 9 1 9 0.755 0.424 0.556 3.39e- 2 0.238 #> 10 1 10 0.498 0.572 0.580 4.96e- 2 0.186 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"function generate n random points inverse pareto distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"","code":"tidy_inverse_pareto(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":".n number randomly generated points want. .shape Must positive. .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"function uses underlying actuar::rinvpareto(), underlying p, d, q functions. information please see actuar::rinvpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"","code":"tidy_inverse_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 4.07 -2.09 0.00140 0 0.0513 #> 2 1 2 0.512 -0.310 0.199 0.02 0.00602 #> 3 1 3 1.11 1.47 0.194 0.0392 0.0134 #> 4 1 4 0.108 3.25 0.0740 0.0577 0.00112 #> 5 1 5 0.0590 5.03 0.0227 0.0755 0.000532 #> 6 1 6 0.306 6.81 0.00741 0.0926 0.00351 #> 7 1 7 0.0178 8.59 0.00764 0.109 0.0000354 #> 8 1 8 2.19 10.4 0.00306 0.125 0.0269 #> 9 1 9 7.97 12.2 0.0186 0.140 0.106 #> 10 1 10 2.88 13.9 0.00106 0.155 0.0357 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"function generate n random points weibull distribution user provided, .shape, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"","code":"tidy_inverse_weibull( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"function uses underlying actuar::rinvweibull(), underlying p, d, q functions. information please see actuar::rinvweibull()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"","code":"tidy_inverse_weibull() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.516 -1.94 0.000590 0 0.270 #> 2 1 2 5.78 -1.59 0.00277 5.24e-22 1.20 #> 3 1 3 0.583 -1.24 0.0104 2.29e-11 0.285 #> 4 1 4 0.638 -0.894 0.0313 8.06e- 8 0.296 #> 5 1 5 0.719 -0.544 0.0759 4.79e- 6 0.312 #> 6 1 6 0.662 -0.195 0.148 5.55e- 5 0.301 #> 7 1 7 0.563 0.155 0.235 2.84e- 4 0.280 #> 8 1 8 2.24 0.504 0.304 9.12e- 4 0.544 #> 9 1 9 0.864 0.854 0.325 2.19e- 3 0.338 #> 10 1 10 0.395 1.20 0.294 4.32e- 3 0.239 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"function takes vector input return kurtosis vector. length vector must least four numbers. kurtosis explains sharpness peak distribution data. ((1/n) * sum(x - mu})^4) / ((()1/n) * sum(x - mu)^2)^2","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"","code":"tidy_kurtosis_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":".x numeric vector length four .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"kurtosis vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"function return kurtosis vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"","code":"tidy_kurtosis_vec(rnorm(100, 3, 2)) #> [1] 3.61924"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"function generate n random points logistic distribution user provided, .location, .scale, number random simulations produced. function returns tibble simulation number column x column corresonds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"","code":"tidy_logistic(.n = 50, .location = 0, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":".n number randomly generated points want. .location location parameter .scale scale parameter .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"function uses underlying stats::rlogis(), underlying p, d, q functions. information please see stats::rlogis()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"","code":"tidy_logistic() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.30 -7.21 0.000218 0.5 1.35 #> 2 1 2 0.953 -6.96 0.000681 0.505 1.11 #> 3 1 3 -1.25 -6.72 0.00182 0.510 -0.0467 #> 4 1 4 0.0612 -6.47 0.00417 0.515 0.598 #> 5 1 5 2.65 -6.22 0.00819 0.520 3.03 #> 6 1 6 1.88 -5.98 0.0138 0.525 1.83 #> 7 1 7 3.03 -5.73 0.0200 0.531 Inf #> 8 1 8 1.65 -5.48 0.0252 0.536 1.62 #> 9 1 9 1.24 -5.23 0.0281 0.541 1.30 #> 10 1 10 -0.525 -4.99 0.0286 0.546 0.303 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"function generate n random points lognormal distribution user provided, .meanlog, .sdlog, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"","code":"tidy_lognormal(.n = 50, .meanlog = 0, .sdlog = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":".n number randomly generated points want. .meanlog Mean distribution log scale default 0 .sdlog Standard deviation distribution log scale default 1 .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"function uses underlying stats::rlnorm(), underlying p, d, q functions. information please see stats::rlnorm()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"","code":"tidy_lognormal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.161 -0.833 0.00167 0 0.0804 #> 2 1 2 0.593 -0.572 0.0180 0.0000497 0.184 #> 3 1 3 1.31 -0.311 0.101 0.000690 0.295 #> 4 1 4 0.137 -0.0498 0.305 0.00261 0.0685 #> 5 1 5 0.208 0.211 0.532 0.00611 0.0982 #> 6 1 6 0.480 0.473 0.600 0.0112 0.163 #> 7 1 7 0.862 0.734 0.516 0.0179 0.228 #> 8 1 8 0.0968 0.995 0.404 0.0258 0 #> 9 1 9 1.37 1.26 0.305 0.0350 0.304 #> 10 1 10 0.654 1.52 0.199 0.0451 0.195 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Mixture Data — tidy_mixture_density","title":"Tidy Mixture Data — tidy_mixture_density","text":"Create mixture model data resulting density line plots.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Mixture Data — tidy_mixture_density","text":"","code":"tidy_mixture_density(...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Mixture Data — tidy_mixture_density","text":"... random data want pass. Example rnorm(50,0,1) something like tidy_normal(.mean = 5, .sd = 1)","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Mixture Data — tidy_mixture_density","text":"list object","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Mixture Data — tidy_mixture_density","text":"function allows make mixture model data. allows produce density data plots data strictly one family one single type distribution given set parameters. example function allow mix say tidy_normal(.mean = 0, .sd = 1) tidy_normal(.mean = 5, .sd = 1) can mix match distributions. output list object three components. Data input_data (random data passed) dist_tbl (tibble passed random data) density_tbl (tibble x y data stats::density()) Plots line_plot - Plots dist_tbl dens_plot - Plots density_tbl Input Functions input_fns - list functions parameters passed function itsefl","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Mixture Data — tidy_mixture_density","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Mixture Data — tidy_mixture_density","text":"","code":"output <- tidy_mixture_density(rnorm(100, 0, 1), tidy_normal(.mean = 5, .sd = 1)) output$data #> $dist_tbl #> # A tibble: 150 × 2 #> x y #> #> 1 1 -1.46 #> 2 2 0.377 #> 3 3 -0.985 #> 4 4 -0.428 #> 5 5 1.48 #> 6 6 0.336 #> 7 7 -0.203 #> 8 8 -0.904 #> 9 9 0.874 #> 10 10 -1.15 #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows #> #> $dens_tbl #> # A tibble: 150 × 2 #> x y #> #> 1 -4.70 0.0000665 #> 2 -4.60 0.0000975 #> 3 -4.51 0.000141 #> 4 -4.41 0.000202 #> 5 -4.31 0.000287 #> 6 -4.21 0.000402 #> 7 -4.12 0.000557 #> 8 -4.02 0.000767 #> 9 -3.92 0.00104 #> 10 -3.83 0.00140 #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows #> #> $input_data #> $input_data$`rnorm(100, 0, 1)` #> [1] -1.45764633 0.37740395 -0.98525730 -0.42757895 1.48025559 0.33648173 #> [7] -0.20254759 -0.90369492 0.87356687 -1.14888225 1.98273812 0.45661303 #> [13] 0.10532920 -0.85134662 -0.23463756 0.85478678 0.47703629 0.39603605 #> [19] -0.38691229 -0.76559233 0.58349930 1.63975939 0.72256044 -0.44474614 #> [25] -0.45722427 0.89424396 -0.09054251 0.48127307 -0.50443319 -1.00143786 #> [31] 0.73671834 0.82206546 0.46452988 -0.60292122 0.63169567 -0.73918488 #> [37] 0.87847070 0.33961531 0.13057424 -0.46233948 0.83831954 0.78476499 #> [43] 0.60425347 -1.02450838 -0.73808104 0.37592464 -1.40906362 -2.18148560 #> [49] 0.26651091 -1.14606077 -0.58491346 0.37524548 -1.33543622 -0.15853331 #> [55] -1.10406359 -0.01263021 0.58985616 -0.54295103 -0.22075551 0.68520410 #> [61] -0.31949967 0.17695608 1.42407026 -0.45439977 -1.74227079 0.64187271 #> [67] -0.67540187 -1.51419692 1.26074451 0.07059006 1.01969872 -1.70322658 #> [73] -1.73616903 -0.56666579 1.49017136 -1.21986354 0.28965875 -1.30375760 #> [79] 0.80406191 -0.15991238 0.88963136 1.81352891 -1.00660338 -0.78754881 #> [85] -1.16911414 1.51560301 -0.06941478 1.75925122 -0.66947848 -1.34217013 #> [91] -0.40929426 0.08412376 -0.22633675 2.04540415 1.05329515 -0.04635191 #> [97] -0.20232170 -0.79151517 1.97345656 1.23334517 #> #> $input_data$`tidy_normal(.mean = 5, .sd = 1)` #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 4.29 1.73 0.000244 0.000000287 4.50 #> 2 1 2 3.99 1.87 0.000652 0.000000319 4.28 #> 3 1 3 6.41 2.01 0.00157 0.000000354 5.84 #> 4 1 4 5.25 2.15 0.00340 0.000000393 5.07 #> 5 1 5 4.50 2.29 0.00670 0.000000436 4.63 #> 6 1 6 4.21 2.42 0.0120 0.000000484 4.45 #> 7 1 7 3.60 2.56 0.0199 0.000000537 3.95 #> 8 1 8 4.48 2.70 0.0307 0.000000595 4.62 #> 9 1 9 3.24 2.84 0.0448 0.000000660 3.48 #> 10 1 10 3.79 2.98 0.0629 0.000000731 4.13 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows #> #> output$plots #> $line_plot #> #> $dens_plot #> output$input_fns #> [[1]] #> rnorm(100, 0, 1) #> #> [[2]] #> tidy_normal(.mean = 5, .sd = 1) #>"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"","code":"tidy_multi_dist_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":".data data passed function tidy_multi_dist() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"","code":"tn <- tidy_multi_single_dist( .tidy_dist = \"tidy_normal\", .param_list = list( .n = 500, .mean = c(-2, 0, 2), .sd = 1, .num_sims = 5 ) ) tn %>% tidy_multi_dist_autoplot() tn %>% tidy_multi_dist_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Generate multiple distributions data tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"","code":"tidy_multi_single_dist(.tidy_dist = NULL, .param_list = list())"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":".tidy_dist type tidy_ distribution want run. can choose one. .param_list must list() object parameters want pass TidyDensity tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Generate multiple distributions data tidy_ distribution function. allows simulate multiple distributions family order view shapes change parameter changes. can visualize differences however choose.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"","code":"tidy_multi_single_dist( .tidy_dist = \"tidy_normal\", .param_list = list( .n = 50, .mean = c(-1, 0, 1), .sd = 1, .num_sims = 3 ) ) #> # A tibble: 450 × 8 #> sim_number dist_name x y dx dy p q #> #> 1 1 Gaussian c(-1, 1) 1 -0.969 -4.67 0.000280 0.841 -0.726 #> 2 1 Gaussian c(-1, 1) 2 -0.444 -4.54 0.000857 0.846 -0.399 #> 3 1 Gaussian c(-1, 1) 3 -0.877 -4.41 0.00226 0.851 -0.672 #> 4 1 Gaussian c(-1, 1) 4 -3.36 -4.28 0.00517 0.856 -2.48 #> 5 1 Gaussian c(-1, 1) 5 -1.19 -4.15 0.0103 0.860 -0.856 #> 6 1 Gaussian c(-1, 1) 6 -0.767 -4.02 0.0177 0.865 -0.605 #> 7 1 Gaussian c(-1, 1) 7 -0.798 -3.88 0.0268 0.869 -0.624 #> 8 1 Gaussian c(-1, 1) 8 -1.98 -3.75 0.0358 0.873 -1.30 #> 9 1 Gaussian c(-1, 1) 9 -2.13 -3.62 0.0426 0.878 -1.39 #> 10 1 Gaussian c(-1, 1) 10 -1.29 -3.49 0.0459 0.882 -0.910 #> # … with 440 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"function generate n random points negative binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"","code":"tidy_negative_binomial(.n = 50, .size = 1, .prob = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":".n number randomly generated points want. .size target number successful trials, dispersion parameter (shape parameter gamma mixing distribution). Must strictly positive, need integer. .prob Probability success trial 0 < .prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"function uses underlying stats::rnbinom(), underlying p, d, q functions. information please see stats::rnbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"","code":"tidy_negative_binomial() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 -10.1 0.000211 0.1 0 #> 2 1 2 1 -8.70 0.000733 0.1 0 #> 3 1 3 13 -7.27 0.00214 0.1 2 #> 4 1 4 4 -5.83 0.00531 0.1 0 #> 5 1 5 19 -4.40 0.0112 0.1 4 #> 6 1 6 2 -2.97 0.0201 0.1 0 #> 7 1 7 10 -1.53 0.0311 0.1 2 #> 8 1 8 0 -0.0970 0.0419 0.1 0 #> 9 1 9 9 1.34 0.0498 0.1 1 #> 10 1 10 14 2.77 0.0531 0.1 3 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"function generate n random points Gaussian distribution user provided, .mean, .sd - standard deviation number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, dnorm, pnorm qnorm data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"","code":"tidy_normal(.n = 50, .mean = 0, .sd = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":".n number randomly generated points want. .mean mean randomly generated data. .sd standard deviation randomly generated data. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"function uses underlying stats::rnorm(), stats::pnorm(), stats::qnorm() functions generate data given parameters. information please see stats::rnorm()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"","code":"tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.541 -3.23 0.000263 0.5 0.532 #> 2 1 2 0.0293 -3.10 0.000693 0.508 0.170 #> 3 1 3 1.25 -2.98 0.00165 0.516 1.22 #> 4 1 4 -0.480 -2.86 0.00358 0.524 -0.169 #> 5 1 5 0.208 -2.74 0.00708 0.533 0.292 #> 6 1 6 -0.411 -2.61 0.0128 0.541 -0.123 #> 7 1 7 -0.271 -2.49 0.0214 0.549 -0.0297 #> 8 1 8 0.496 -2.37 0.0329 0.557 0.498 #> 9 1 9 1.05 -2.25 0.0471 0.565 0.978 #> 10 1 10 1.67 -2.12 0.0630 0.573 Inf #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"function generate n random points paralogistic distribution user provided, .shape, .rate, .scale number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"","code":"tidy_paralogistic( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"function uses underlying actuar::rparalogis(), underlying p, d, q functions. information please see actuar::rparalogis()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"","code":"tidy_paralogistic() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.52 -2.50 0.000781 0 0.0632 #> 2 1 2 1.05 -1.88 0.00673 0.0200 0.0427 #> 3 1 3 0.0441 -1.26 0.0352 0.0392 0.00130 #> 4 1 4 8.06 -0.639 0.114 0.0577 0.467 #> 5 1 5 0.505 -0.0196 0.232 0.0755 0.0199 #> 6 1 6 0.908 0.599 0.301 0.0926 0.0367 #> 7 1 7 1.01 1.22 0.253 0.109 0.0409 #> 8 1 8 0.628 1.84 0.148 0.125 0.0250 #> 9 1 9 0.583 2.46 0.0808 0.140 0.0231 #> 10 1 10 9.04 3.08 0.0594 0.155 0.554 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"function generate n random points pareto distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"","code":"tidy_pareto(.n = 50, .shape = 10, .scale = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":".n number randomly generated points want. .shape Must positive. .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"function uses underlying actuar::rpareto(), underlying p, d, q functions. information please see actuar::rpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"","code":"tidy_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0148 -0.0106 0.197 0 0.00592 #> 2 1 2 0.00477 -0.00947 0.511 0.844 0.00149 #> 3 1 3 0.000380 -0.00834 1.21 0.967 0.0000619 #> 4 1 4 0.000407 -0.00722 2.61 0.992 0.0000700 #> 5 1 5 0.00554 -0.00610 5.15 0.997 0.00177 #> 6 1 6 0.00304 -0.00498 9.31 0.999 0.000901 #> 7 1 7 0.00669 -0.00386 15.4 1.00 0.00219 #> 8 1 8 0.00222 -0.00274 23.4 1.00 0.000634 #> 9 1 9 0.0180 -0.00162 32.8 1.00 0.00790 #> 10 1 10 0.00438 -0.000497 42.3 1.00 0.00136 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"function generate n random points single parameter pareto distribution user provided, .shape, .min, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"","code":"tidy_pareto1(.n = 50, .shape = 1, .min = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":".n number randomly generated points want. .shape Must positive. .min lower bound support distribution. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"function uses underlying actuar::rpareto1(), underlying p, d, q functions. information please see actuar::rpareto1()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"","code":"tidy_pareto1() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.03 -1.86 3.09e- 3 0 1.00 #> 2 1 2 1.47 12.2 3.46e- 3 0 1.00 #> 3 1 3 1.88 26.3 3.51e- 3 0 1.00 #> 4 1 4 5.76 40.4 0 0 1.01 #> 5 1 5 1.91 54.5 0 0 1.00 #> 6 1 6 1.48 68.6 1.82e-18 0 1.00 #> 7 1 7 7.70 82.6 1.49e-15 0 1.01 #> 8 1 8 3.64 96.7 7.14e-10 0 1.00 #> 9 1 9 685. 111. 2.12e-18 0 Inf #> 10 1 10 1.44 125. 0 0 1.00 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"function generate n random points Poisson distribution user provided, .lambda, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"","code":"tidy_poisson(.n = 50, .lambda = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":".n number randomly generated points want. .lambda vector non-negative means. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"function uses underlying stats::rpois(), underlying p, d, q functions. information please see stats::rpois()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"","code":"tidy_poisson() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 3 -1.49 0.00253 0.368 2 #> 2 1 2 2 -1.35 0.00572 0.368 1 #> 3 1 3 0 -1.21 0.0119 0.368 0 #> 4 1 4 2 -1.06 0.0229 0.368 1 #> 5 1 5 0 -0.922 0.0406 0.368 0 #> 6 1 6 2 -0.779 0.0664 0.368 1 #> 7 1 7 1 -0.637 0.100 0.368 0 #> 8 1 8 0 -0.494 0.140 0.368 0 #> 9 1 9 3 -0.352 0.181 0.368 2 #> 10 1 10 4 -0.209 0.219 0.368 Inf #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Random Walk — tidy_random_walk","title":"Tidy Random Walk — tidy_random_walk","text":"Takes data tidy_ distribution function applies random walk calculation either cum_prod cum_sum y.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Random Walk — tidy_random_walk","text":"","code":"tidy_random_walk( .data, .initial_value = 0, .sample = FALSE, .replace = FALSE, .value_type = \"cum_prod\" )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Random Walk — tidy_random_walk","text":".data data passed tidy_ distribution function. .initial_value default 0, can set whatever want. .sample boolean value TRUE/FALSE. default FALSE. set TRUE y value tidy_ distribution function sampled. .replace boolean value TRUE/FALSE. default FALSE. set TRUE .sample set TRUE replace parameter sample function set TRUE. .value_type can take one three different values now. following: \"cum_prod\" - take cumprod y \"cum_sum\" - take cumsum y","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Random Walk — tidy_random_walk","text":"ungrouped tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Random Walk — tidy_random_walk","text":"Monte Carlo simulations first formally designed 1940’s developing nuclear weapons, since heavily used various fields use randomness solve problems potentially deterministic nature. finance, Monte Carlo simulations can useful tool give sense assets certain characteristics might behave future. complex sophisticated financial forecasting methods ARIMA (Auto-Regressive Integrated Moving Average) GARCH (Generalised Auto-Regressive Conditional Heteroskedasticity) attempt model randomness underlying macro factors seasonality volatility clustering, Monte Carlo random walks work surprisingly well illustrating market volatility long results taken seriously.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Random Walk — tidy_random_walk","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Random Walk — tidy_random_walk","text":"","code":"tidy_normal(.sd = .1, .num_sims = 25) %>% tidy_random_walk() #> # A tibble: 1,250 × 8 #> sim_number x y dx dy p q random_walk_value #> #> 1 1 1 0.0948 -0.313 0.00303 0.5 0.0444 0.0948 #> 2 1 2 0.0503 -0.299 0.00804 0.581 0.0166 0.150 #> 3 1 3 0.0727 -0.286 0.0193 0.658 0.0303 0.233 #> 4 1 4 -0.128 -0.272 0.0423 0.730 -0.107 0.0759 #> 5 1 5 0.0894 -0.258 0.0844 0.793 0.0409 0.172 #> 6 1 6 0.137 -0.244 0.155 0.846 0.0747 0.333 #> 7 1 7 -0.121 -0.231 0.263 0.890 -0.100 0.171 #> 8 1 8 -0.0913 -0.217 0.417 0.923 -0.0741 0.0643 #> 9 1 9 -0.0903 -0.203 0.623 0.949 -0.0733 -0.0318 #> 10 1 10 0.00239 -0.190 0.882 0.967 -0.0120 -0.0295 #> # … with 1,240 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"auto-plotting function take tidy_ distribution function arguments regard output visualization. number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"","code":"tidy_random_walk_autoplot( .data, .line_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .line_size size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"function produce simple random walk plot tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"","code":"tidy_normal(.sd = .1, .num_sims = 5) %>% tidy_random_walk(.value_type = \"cum_sum\") %>% tidy_random_walk_autoplot() tidy_normal(.sd = .1, .num_sims = 20) %>% tidy_random_walk(.value_type = \"cum_sum\", .sample = TRUE, .replace = TRUE) %>% tidy_random_walk_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the range statistic — tidy_range_statistic","title":"Get the range statistic — tidy_range_statistic","text":"Takes numeric vector returns back range vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the range statistic — tidy_range_statistic","text":"","code":"tidy_range_statistic(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the range statistic — tidy_range_statistic","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the range statistic — tidy_range_statistic","text":"single number, range statistic","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the range statistic — tidy_range_statistic","text":"Takes numeric vector returns range vector using diff range functions.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get the range statistic — tidy_range_statistic","text":"Steven P. Sandeson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the range statistic — tidy_range_statistic","text":"","code":"tidy_range_statistic(seq(1:10)) #> [1] 9"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Takes numeric vector return vector scaled [0,1]","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"","code":"tidy_scale_zero_one_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":".x numeric vector scaled [0,1] inclusive.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Takes numeric vector return vector scaled [0,1] input vector must numeric. computation fairly straightforward. may helpful trying compare distributions data distribution like beta requires data 0 1 $$y[h] = (x - min(x))/(max(x) - min(x))$$","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"","code":"vec_1 <- rnorm(100, 2, 1) vec_2 <- tidy_scale_zero_one_vec(vec_1) dens_1 <- density(vec_1) dens_2 <- density(vec_2) max_x <- max(dens_1$x, dens_2$x) max_y <- max(dens_1$y, dens_2$y) plot(dens_1, asp = max_y/max_x, main = \"Density vec_1 (Red) and vec_2 (Blue)\", col = \"red\", xlab = \"\", ylab = \"Density of Vec 1 and Vec 2\") lines(dens_2, col = \"blue\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Skewness of a Vector — tidy_skewness_vec","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"function takes vector input return skewness vector. length vector must least four numbers. skewness explains 'tailedness' distribution data. ((1/n) * sum(x - mu})^3) / ((()1/n) * sum(x - mu)^2)^(3/2)","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"","code":"tidy_skewness_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":".x numeric vector length four .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"skewness vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"function return skewness vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"","code":"tidy_skewness_vec(rnorm(100, 3, 2)) #> [1] 0.09061656"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated T Distribution Tibble — tidy_t","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"function generate n random points rt distribution user provided, df, ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"","code":"tidy_t(.n = 50, .df = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":".n number randomly generated points want. .df Degrees freedom, Inf allowed. .ncp Non-centrality parameter. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"function uses underlying stats::rt(), underlying p, d, q functions. information please see stats::rt()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"","code":"tidy_t() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 -1.07 -36.4 0.000178 0.5 0.869 #> 2 1 2 -11.8 -35.4 0.00796 0.506 -0.0147 #> 3 1 3 2.87 -34.4 0.0111 0.513 1.50 #> 4 1 4 0.0326 -33.4 0.000469 0.519 1.01 #> 5 1 5 -0.581 -32.4 0.000000617 0.526 0.929 #> 6 1 6 1.41 -31.4 0.000000411 0.532 1.22 #> 7 1 7 3.83 -30.3 0.000362 0.539 1.73 #> 8 1 8 -0.324 -29.3 0.0103 0.545 0.962 #> 9 1 9 -2.16 -28.3 0.00874 0.552 0.747 #> 10 1 10 0.788 -27.3 0.000224 0.558 1.12 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"function generate n random points uniform distribution user provided, .min .max values, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"","code":"tidy_uniform(.n = 50, .min = 0, .max = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":".n number randomly generated points want. .min lower limit distribution. .max upper limit distribution .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"function uses underlying stats::runif(), underlying p, d, q functions. information please see stats::runif()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"","code":"tidy_uniform() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.938 -0.339 0.00213 0 0.946 #> 2 1 2 0.641 -0.305 0.00512 0.0204 0.643 #> 3 1 3 0.910 -0.270 0.0113 0.0408 0.917 #> 4 1 4 0.375 -0.236 0.0230 0.0612 0.373 #> 5 1 5 0.206 -0.202 0.0431 0.0816 0.200 #> 6 1 6 0.380 -0.168 0.0749 0.102 0.378 #> 7 1 7 0.830 -0.133 0.121 0.122 0.836 #> 8 1 8 0.643 -0.0992 0.182 0.143 0.646 #> 9 1 9 0.0131 -0.0649 0.256 0.163 0.00418 #> 10 1 10 0.688 -0.0307 0.340 0.184 0.691 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"function generate n random points weibull distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"","code":"tidy_weibull(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":".n number randomly generated points want. .shape Shape parameter defaults 0. .scale Scale parameter defaults 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"function uses underlying stats::rweibull(), underlying p, d, q functions. information please see stats::rweibull()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"","code":"tidy_weibull() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2.53 -1.37 0.00130 0 0.557 #> 2 1 2 2.15 -1.20 0.00424 0.0202 0.450 #> 3 1 3 0.505 -1.02 0.0120 0.0400 0.0867 #> 4 1 4 1.95 -0.843 0.0299 0.0594 0.397 #> 5 1 5 0.952 -0.666 0.0646 0.0784 0.173 #> 6 1 6 0.177 -0.489 0.122 0.0970 0.0277 #> 7 1 7 0.139 -0.312 0.203 0.115 0.0210 #> 8 1 8 2.23 -0.135 0.297 0.133 0.472 #> 9 1 9 1.17 0.0414 0.385 0.151 0.217 #> 10 1 10 1.26 0.218 0.447 0.168 0.238 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"function generate n random points zero truncated binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"","code":"tidy_zero_truncated_binomial(.n = 50, .size = 0, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial 0 <= prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"function uses underlying actuar::rztbinom(), underlying p, d, q functions. information please see actuar::rztbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"","code":"tidy_zero_truncated_binomial() #> Warning: NaNs produced #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 NaN NaN #> 2 1 2 0 -1.18 0.0156 NaN NaN #> 3 1 3 0 -1.13 0.0220 NaN NaN #> 4 1 4 0 -1.08 0.0305 NaN NaN #> 5 1 5 0 -1.03 0.0418 NaN NaN #> 6 1 6 0 -0.983 0.0564 NaN NaN #> 7 1 7 0 -0.932 0.0749 NaN NaN #> 8 1 8 0 -0.882 0.0981 NaN NaN #> 9 1 9 0 -0.832 0.126 NaN NaN #> 10 1 10 0 -0.781 0.161 NaN NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"function generate n random points zero truncated Geometric distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"","code":"tidy_zero_truncated_geometric(.n = 50, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":".n number randomly generated points want. .prob probability success trial 0 < prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"function uses underlying actuar::rztgeom(), underlying p, d, q functions. information please see actuar::rztgeom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"","code":"tidy_zero_truncated_geometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 -0.235 0.0109 0 NaN #> 2 1 2 1 -0.184 0.0156 0 NaN #> 3 1 3 1 -0.134 0.0220 0 NaN #> 4 1 4 1 -0.0835 0.0305 0 NaN #> 5 1 5 1 -0.0331 0.0418 0 NaN #> 6 1 6 1 0.0173 0.0564 0 NaN #> 7 1 7 1 0.0677 0.0749 0 NaN #> 8 1 8 1 0.118 0.0981 0 NaN #> 9 1 9 1 0.168 0.126 0 NaN #> 10 1 10 1 0.219 0.161 0 NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"function generate n random points zero truncated binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"","code":"tidy_zero_truncated_negative_binomial( .n = 50, .size = 0, .prob = 1, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial 0 <= prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"function uses underlying actuar::rztnbinom(), underlying p, d, q functions. information please see actuar::rztnbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"","code":"tidy_zero_truncated_binomial() #> Warning: NaNs produced #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 NaN NaN #> 2 1 2 0 -1.18 0.0156 NaN NaN #> 3 1 3 0 -1.13 0.0220 NaN NaN #> 4 1 4 0 -1.08 0.0305 NaN NaN #> 5 1 5 0 -1.03 0.0418 NaN NaN #> 6 1 6 0 -0.983 0.0564 NaN NaN #> 7 1 7 0 -0.932 0.0749 NaN NaN #> 8 1 8 0 -0.882 0.0981 NaN NaN #> 9 1 9 0 -0.832 0.126 NaN NaN #> 10 1 10 0 -0.781 0.161 NaN NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"function generate n random points Zero Truncated Poisson distribution user provided, .lambda, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"","code":"tidy_zero_truncated_poisson(.n = 50, .lambda = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":".n number randomly generated points want. .lambda vector non-negative means. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"function uses underlying actuar::rztpois(), underlying p, d, q functions. information please see actuar::rztpois()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"","code":"tidy_zero_truncated_poisson() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 0.0923 0.00890 0 1 #> 2 1 2 2 0.191 0.0223 0 1 #> 3 1 3 2 0.289 0.0504 0 1 #> 4 1 4 1 0.387 0.102 0 1 #> 5 1 5 1 0.485 0.187 0 1 #> 6 1 6 1 0.584 0.308 0 1 #> 7 1 7 1 0.682 0.456 0 1 #> 8 1 8 3 0.780 0.608 0 2 #> 9 1 9 2 0.879 0.730 0 1 #> 10 1 10 3 0.977 0.790 0 2 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Beta Parameters — util_beta_param_estimate","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"function automatically scale data 0 1 already. means can pass vector like mtcars$mpg worry . function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated beta data. Three different methods shape parameters supplied: Bayes NIST mme EnvStats mme, see EnvStats::ebeta()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"","code":"util_beta_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Beta Parameters — util_beta_param_estimate","text":".x vector data passed function. Must numeric, values must 0 <= x <= 1 .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"function attempt estimate beta shape1 shape2 parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_beta_param_estimate(x) #> For the beta distribution, its mean 'mu' should be 0 < mu < 1. The data will #> therefore be scaled to enforce this. output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> #> 1 Beta 32 10.4 33.9 0.412 0.0658 Bayes 13.2 18.8 0.702 #> 2 Beta 32 10.4 33.9 0.412 0.0658 NIST_MME 1.11 1.58 0.702 #> 3 Beta 32 10.4 33.9 0.412 0.0658 EnvStats… 1.16 1.65 0.702 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() tb <- rbeta(50, 2.5, 1.4) util_beta_param_estimate(tb)$parameter_tbl #> There was no need to scale the data. #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> #> 1 Beta 50 0.199 0.991 0.650 0.0419 Bayes 32.5 17.5 1.86 #> 2 Beta 50 0.199 0.991 0.650 0.0419 NIST_MME 2.88 1.55 1.86 #> 3 Beta 50 0.199 0.991 0.650 0.0419 EnvStats… 2.95 1.59 1.86 #> # … with abbreviated variable name ¹​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_beta_stats_tbl","title":"Distribution Statistics — util_beta_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_beta_stats_tbl","text":"","code":"util_beta_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_beta_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_beta_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_beta_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_beta_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_beta_stats_tbl","text":"","code":"library(dplyr) tidy_beta() %>% util_beta_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_beta\" #> $ function_call \"Beta c(1, 1, 0)\" #> $ distribution \"Beta\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.5 #> $ mode \"undefined\" #> $ range \"0 to 1\" #> $ std_dv 0.2886751 #> $ coeff_var 0.5773503 #> $ skewness 0 #> $ kurtosis NA #> $ computed_std_skew 0.01144016 #> $ computed_std_kurt 1.96805 #> $ ci_lo 0.04156415 #> $ ci_hi 0.9507906"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Binomial Parameters — util_binomial_param_estimate","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"function check see given vector .x either numeric vector factor vector least two levels cause error function abort. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated binomial data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"","code":"util_binomial_param_estimate(.x, .size = NULL, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":".x vector data passed function. Must numeric, values must 0 <= x <= 1 .size Number trials, zero . .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"function attempt estimate binomial p_hat size parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tb <- rbinom(50, 1, .1) output <- util_binomial_param_estimate(tb) output$parameter_tbl #> # A tibble: 1 × 10 #> dist_type samp_size min max mean variance method prob size shape…¹ #> #> 1 Binomial 50 0 1 0.14 0.123 EnvStats_M… 0.14 50 0.0028 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_binomial_stats_tbl","title":"Distribution Statistics — util_binomial_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_binomial_stats_tbl","text":"","code":"util_binomial_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_binomial_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_binomial_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_binomial_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_binomial_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_binomial_stats_tbl","text":"","code":"library(dplyr) tidy_binomial() %>% util_binomial_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_binomial\" #> $ function_call \"Binomial c(0, 1)\" #> $ distribution \"Binomial\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode_lower 0 #> $ mode_upper 1 #> $ range \"0 to 0\" #> $ std_dv 0 #> $ coeff_var NaN #> $ skewness -Inf #> $ kurtosis NaN #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Cauchy Parameters — util_cauchy_param_estimate","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated cauchy data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"","code":"util_cauchy_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"function attempt estimate cauchy location scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_cauchy(.location = 0, .scale = 1)$y output <- util_cauchy_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max method location scale ratio #> #> 1 Cauchy 50 -72.2 339. MASS -0.0681 2.65 -0.0257 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_cauchy_stats_tbl","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"","code":"util_cauchy_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_cauchy_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"","code":"library(dplyr) tidy_cauchy() %>% util_cauchy_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_cauchy\" #> $ function_call \"Cauchy c(0, 1)\" #> $ distribution \"Cauchy\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean \"undefined\" #> $ median 0 #> $ mode 0 #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness 0 #> $ kurtosis \"undefined\" #> $ computed_std_skew 2.03255 #> $ computed_std_kurt 13.14494 #> $ ci_lo -12.21519 #> $ ci_hi 17.1068"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_chisquare_stats_tbl","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"","code":"util_chisquare_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_chisquare_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"","code":"library(dplyr) tidy_chisquare() %>% util_chisquare_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_chisquare\" #> $ function_call \"Chisquare c(1, 1)\" #> $ distribution \"Chisquare\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ median 0.3333333 #> $ mode \"undefined\" #> $ std_dv 1.414214 #> $ coeff_var 1.414214 #> $ skewness 2.828427 #> $ kurtosis 15 #> $ computed_std_skew 2.608379 #> $ computed_std_kurt 10.17601 #> $ ci_lo 0.0388085 #> $ ci_hi 7.210262"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Exponential Parameters — util_exponential_param_estimate","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"function attempt estimate exponential rate parameter given vector values. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated exponential data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"","code":"util_exponential_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":".x vector data passed function. Must numeric. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"function see given vector .x numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"","code":"library(dplyr) library(ggplot2) te <- tidy_exponential(.rate = .1) %>% pull(y) output <- util_exponential_param_estimate(te) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max mean variance method rate #> #> 1 Exponential 50 0.340 43.6 10.3 113. NIST_MME 0.0969 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_exponential_stats_tbl","title":"Distribution Statistics — util_exponential_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_exponential_stats_tbl","text":"","code":"util_exponential_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_exponential_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_exponential_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_exponential_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_exponential_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_exponential_stats_tbl","text":"","code":"library(dplyr) tidy_exponential() %>% util_exponential_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_exponential\" #> $ function_call \"Exponential c(1)\" #> $ distribution \"Exponential\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ median 0.6931472 #> $ mode 1 #> $ range \"1 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 2 #> $ kurtosis 9 #> $ computed_std_skew 3.937832 #> $ computed_std_kurt 22.3348 #> $ ci_lo 0.05862891 #> $ ci_hi 3.370082"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_f_stats_tbl","title":"Distribution Statistics — util_f_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_f_stats_tbl","text":"","code":"util_f_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_f_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_f_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_f_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_f_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_f_stats_tbl","text":"","code":"library(dplyr) tidy_f() %>% util_f_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_f\" #> $ function_call \"F Distribution c(1, 1, 0)\" #> $ distribution \"F\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean \"undefined\" #> $ median \"Not computed\" #> $ mode \"undefined\" #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness \"undefined\" #> $ kurtosis \"Not computed\" #> $ computed_std_skew 6.360531 #> $ computed_std_kurt 43.20686 #> $ ci_lo 0.005427014 #> $ ci_hi 200.4485"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Gamma Parameters — util_gamma_param_estimate","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"function attempt estimate gamma shape scale parameters given vector values. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated gamma data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"","code":"util_gamma_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":".x vector data passed function. Must numeric. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"function see given vector .x numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tg <- tidy_gamma(.shape = 1, .scale = .3) %>% pull(y) output <- util_gamma_param_estimate(tg) output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape scale shape…¹ #> #> 1 Gamma 50 0.00150 1.31 0.301 0.264 NIST_MME 1.30 0.232 5.61 #> 2 Gamma 50 0.00150 1.31 0.301 0.264 EnvStats… 1.27 0.232 5.50 #> 3 Gamma 50 0.00150 1.31 0.301 0.264 EnvStats… 1.24 0.232 5.33 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_gamma_stats_tbl","title":"Distribution Statistics — util_gamma_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_gamma_stats_tbl","text":"","code":"util_gamma_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_gamma_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_gamma_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_gamma_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_gamma_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_gamma_stats_tbl","text":"","code":"library(dplyr) tidy_gamma() %>% util_gamma_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_gamma\" #> $ function_call \"Gamma c(1, 0.3)\" #> $ distribution \"Gamma\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 2 #> $ kurtosis 9 #> $ computed_std_skew 1.712431 #> $ computed_std_kurt 6.524924 #> $ ci_lo 0.005972779 #> $ ci_hi 1.119421"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Geometric Parameters — util_geometric_param_estimate","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"function attempt estimate geometric prob parameter given vector values .x. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated geometric data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"","code":"util_geometric_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":".x vector data passed function. Must non-negative integers. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"function see given vector .x numeric vector. attempt estimate prob parameter geometric distribution.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tg <- tidy_geometric(.prob = .1) %>% pull(y) output <- util_geometric_param_estimate(tg) output$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean variance sum_x method shape #> #> 1 Geometric 50 0 24 6.24 31.9 312 EnvStats_MME 0.138 #> 2 Geometric 50 0 24 6.24 31.9 312 EnvStats_MVUE 0.136 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_geometric_stats_tbl","title":"Distribution Statistics — util_geometric_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_geometric_stats_tbl","text":"","code":"util_geometric_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_geometric_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_geometric_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_geometric_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_geometric_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_geometric_stats_tbl","text":"","code":"library(dplyr) tidy_geometric() %>% util_geometric_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_geometric\" #> $ function_call \"Geometric c(1)\" #> $ distribution \"Geometric\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 0 #> $ coeff_var 0 #> $ skewness Inf #> $ kurtosis Inf #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"function attempt estimate geometric prob parameter given vector values .x. Estimate m, number white balls urn, m+n, total number balls urn, hypergeometric distribution.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"","code":"util_hypergeometric_param_estimate( .x, .m = NULL, .total = NULL, .k, .auto_gen_empirical = TRUE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":".x non-negative integer indicating number white balls sample size .k drawn without replacement urn. missing, undefined infinite values. .m Non-negative integer indicating number white balls urn. must supply .m .total, . missing values. .total positive integer indicating total number balls urn (.e., m+n). must supply .m .total, . missing values. .k positive integer indicating number balls drawn without replacement urn. missing values. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"function see given vector .x numeric integer. attempt estimate prob parameter geometric distribution. Missing (NA), undefined (NaN), infinite (Inf, -Inf) values allowed. Let .x observation hypergeometric distribution parameters .m = M, .n = N, .k = K. R nomenclature, .x represents number white balls drawn sample .k balls drawn without replacement urn containing .m white balls .n black balls. total number balls urn thus .m + .n. Denote total number balls T = .m + .n","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"","code":"library(dplyr) library(ggplot2) th <- rhyper(10, 20, 30, 5) output <- util_hypergeometric_param_estimate(th, .total = 50, .k = 5) output$parameter_tbl #> # A tibble: 2 × 5 #> dist_type samp_size method m total #> #> 1 Hypergeometric 10 EnvStats_MLE 20.4 NA #> 2 Hypergeometric 10 EnvStats_MVUE 20 50 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_hypergeometric_stats_tbl","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"","code":"util_hypergeometric_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"","code":"library(dplyr) tidy_hypergeometric() %>% util_hypergeometric_stats_tbl() %>% glimpse() #> Warning: NaNs produced #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_hypergeometric\" #> $ function_call \"Hypergeometric c(0, 0, 0)\" #> $ distribution \"Hypergeometric\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean NaN #> $ mode_lower -0.5 #> $ mode_upper 0.5 #> $ range \"0 to Inf\" #> $ std_dv NaN #> $ coeff_var NaN #> $ skewness NaN #> $ kurtosis NaN #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Logistic Parameters — util_logistic_param_estimate","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated logistic data. Three different methods shape parameters supplied: MLE MME MMUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"","code":"util_logistic_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"function attempt estimate logistic location scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_logistic_param_estimate(x) output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> #> 1 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 3.27 6.14 #> 2 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 3.32 6.05 #> 3 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 12.6 1.60 #> # … with abbreviated variable names ¹​location, ²​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() t <- rlogis(50, 2.5, 1.4) util_logistic_param_estimate(t)$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> #> 1 Logistic 50 -8.65 5.85 1.94 1.38 EnvSt… 1.94 1.38 1.41 #> 2 Logistic 50 -8.65 5.85 1.94 1.38 EnvSt… 1.94 1.39 1.39 #> 3 Logistic 50 -8.65 5.85 1.94 1.38 EnvSt… 1.94 1.49 1.30 #> # … with abbreviated variable names ¹​location, ²​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_logistic_stats_tbl","title":"Distribution Statistics — util_logistic_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_logistic_stats_tbl","text":"","code":"util_logistic_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_logistic_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_logistic_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_logistic_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_logistic_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_logistic_stats_tbl","text":"","code":"library(dplyr) tidy_logistic() %>% util_logistic_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_logistic\" #> $ function_call \"Logistic c(0, 1)\" #> $ distribution \"Logistic\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode_lower 0 #> $ range \"0 to Inf\" #> $ std_dv 1.813799 #> $ coeff_var 3.289868 #> $ skewness 0 #> $ kurtosis 1.2 #> $ computed_std_skew 0.1404616 #> $ computed_std_kurt 2.854101 #> $ ci_lo -4.024896 #> $ ci_hi 3.746533"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Lognormal Parameters — util_lognormal_param_estimate","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated lognormal data. Three different methods shape parameters supplied: mme, see EnvStats::elnorm() mle, see EnvStats::elnorm()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"","code":"util_lognormal_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"function attempt estimate lognormal meanlog log sd parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_lognormal_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> #> 1 Lognormal 32 10.4 33.9 EnvStats_MVUE 2.96 0.298 9.93 #> 2 Lognormal 32 10.4 33.9 EnvStats_MME 2.96 0.293 10.1 output$combined_data_tbl %>% tidy_combined_autoplot() tb <- tidy_lognormal(.meanlog = 2, .sdlog = 1) %>% pull(y) util_lognormal_param_estimate(tb)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> #> 1 Lognormal 50 1.42 75.8 EnvStats_MVUE 2.36 0.974 2.42 #> 2 Lognormal 50 1.42 75.8 EnvStats_MME 2.36 0.964 2.45"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_lognormal_stats_tbl","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"","code":"util_lognormal_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_lognormal_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"","code":"library(dplyr) tidy_lognormal() %>% util_lognormal_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_lognormal\" #> $ function_call \"Lognormal c(0, 1)\" #> $ distribution \"Lognormal\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1.648721 #> $ median 1 #> $ mode 0.3678794 #> $ range \"0 to Inf\" #> $ std_dv 2.161197 #> $ coeff_var 1.310832 #> $ skewness 6.184877 #> $ kurtosis 113.9364 #> $ computed_std_skew 1.964519 #> $ computed_std_kurt 7.102225 #> $ ci_lo 0.2020056 #> $ ci_hi 5.006112"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated negative binomial data. Two different methods shape parameters supplied: MLE/MME MMUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"","code":"util_negative_binomial_param_estimate(.x, .size, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":".x vector data passed function. .size size parameter. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"function attempt estimate negative binomial size prob parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- as.integer(mtcars$mpg) output <- util_negative_binomial_param_estimate(x, .size = 1) output$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean method size prob shape…¹ #> #> 1 Negative Binomial 32 10 33 19.7 EnvStats_M… 32 0.0483 662 #> 2 Negative Binomial 32 10 33 19.7 EnvStats_M… 32 0.0469 682. #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() t <- rnbinom(50, 1, .1) util_negative_binomial_param_estimate(t, .size = 1)$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean method size prob shape…¹ #> #> 1 Negative Binomial 50 0 30 7.76 EnvStats_MM… 50 0.114 438 #> 2 Negative Binomial 50 0 30 7.76 EnvStats_MM… 50 0.112 446. #> # … with abbreviated variable name ¹​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_negative_binomial_stats_tbl","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"","code":"util_negative_binomial_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"","code":"library(dplyr) tidy_negative_binomial() %>% util_negative_binomial_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_negative_binomial\" #> $ function_call \"Negative Binomial c(1, 0.1)\" #> $ distribution \"Negative_binomial\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1111111 #> $ mode_lower 0 #> $ range \"0 to Inf\" #> $ std_dv 0.3513642 #> $ coeff_var 0.1234568 #> $ skewness 3.478505 #> $ kurtosis 14.1 #> $ computed_std_skew 1.601684 #> $ computed_std_kurt 5.293525 #> $ ci_lo 0 #> $ ci_hi 50.3"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated normal data. Three different methods shape parameters supplied: MLE/MME MVUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"","code":"util_normal_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"function attempt estimate normal gaussian mean standard deviation parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_normal_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mu stan_dev shape_ratio #> #> 1 Gaussian 32 10.4 33.9 EnvStats_MME_MLE 20.1 5.93 3.39 #> 2 Gaussian 32 10.4 33.9 EnvStats_MVUE 20.1 6.03 3.33 output$combined_data_tbl %>% tidy_combined_autoplot() t <- rnorm(50, 0, 1) util_normal_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mu stan_dev shape_ratio #> #> 1 Gaussian 50 -1.75 3.49 EnvStats_MME_MLE 0.236 0.993 0.237 #> 2 Gaussian 50 -1.75 3.49 EnvStats_MVUE 0.236 1.00 0.235"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_normal_stats_tbl","title":"Distribution Statistics — util_normal_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_normal_stats_tbl","text":"","code":"util_normal_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_normal_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_normal_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_normal_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_normal_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_normal_stats_tbl","text":"","code":"library(dplyr) tidy_normal() %>% util_normal_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_gaussian\" #> $ function_call \"Gaussian c(0, 1)\" #> $ distribution \"Gaussian\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ median -0.1279899 #> $ mode 0 #> $ std_dv 1 #> $ coeff_var Inf #> $ skewness 0 #> $ kurtosis 3 #> $ computed_std_skew 0.3535038 #> $ computed_std_kurt 2.3906 #> $ ci_lo -1.587755 #> $ ci_hi 1.990075"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Pareto Parameters — util_pareto_param_estimate","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated pareto data. Two different methods shape parameters supplied: LSE MLE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"","code":"util_pareto_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"function attempt estimate pareto shape scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_pareto_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Pareto 32 10.4 33.9 LSE 13.7 2.86 4.79 #> 2 Pareto 32 10.4 33.9 MLE 10.4 1.62 6.40 output$combined_data_tbl %>% tidy_combined_autoplot() t <- tidy_pareto(50, 1, 1) %>% pull(y) util_pareto_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Pareto 50 0.00682 66.5 LSE 0.146 0.496 0.295 #> 2 Pareto 50 0.00682 66.5 MLE 0.00682 0.198 0.0344"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_pareto_stats_tbl","title":"Distribution Statistics — util_pareto_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_pareto_stats_tbl","text":"","code":"util_pareto_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_pareto_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_pareto_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_pareto_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_pareto_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_pareto_stats_tbl","text":"","code":"library(dplyr) tidy_pareto() %>% util_pareto_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_pareto\" #> $ function_call \"Pareto c(10, 0.1)\" #> $ distribution \"Pareto\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1111111 #> $ mode_lower 0.1 #> $ range \"0 to Inf\" #> $ std_dv 0.0124226 #> $ coeff_var 0.000154321 #> $ skewness 2.811057 #> $ kurtosis 14.82857 #> $ computed_std_skew 1.753089 #> $ computed_std_kurt 5.826765 #> $ ci_lo 0.0004801316 #> $ ci_hi 0.03972543"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Poisson Parameters — util_poisson_param_estimate","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated poisson data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"","code":"util_poisson_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"function attempt estimate pareto lambda parameter given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- as.integer(mtcars$mpg) output <- util_poisson_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> #> 1 Posson 32 10 33 MLE 19.7 output$combined_data_tbl %>% tidy_combined_autoplot() t <- rpois(50, 5) util_poisson_param_estimate(t)$parameter_tbl #> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> #> 1 Posson 50 1 12 MLE 4.78"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_poisson_stats_tbl","title":"Distribution Statistics — util_poisson_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_poisson_stats_tbl","text":"","code":"util_poisson_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_poisson_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_poisson_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_poisson_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_poisson_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_poisson_stats_tbl","text":"","code":"library(dplyr) tidy_poisson() %>% util_poisson_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_poisson\" #> $ function_call \"Poisson c(1)\" #> $ distribution \"Poisson\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ mode 1 #> $ range \"0 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 1 #> $ kurtosis 4 #> $ computed_std_skew 0.5824453 #> $ computed_std_kurt 2.221336 #> $ ci_lo 0 #> $ ci_hi 3"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_t_stats_tbl","title":"Distribution Statistics — util_t_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_t_stats_tbl","text":"","code":"util_t_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_t_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_t_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_t_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_t_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_t_stats_tbl","text":"","code":"library(dplyr) tidy_t() %>% util_t_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_t\" #> $ function_call \"T Distribution c(1, 0)\" #> $ distribution \"T\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ median 0 #> $ mode 0 #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness 0 #> $ kurtosis \"undefined\" #> $ computed_std_skew -4.277852 #> $ computed_std_kurt 25.33079 #> $ ci_lo -8.982581 #> $ ci_hi 3.328438"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Uniform Parameters — util_uniform_param_estimate","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated uniform data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"","code":"util_uniform_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"function attempt estimate uniform min max parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_uniform(.min = 1, .max = 3)$y output <- util_uniform_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method min_est max_est ratio #> #> 1 Uniform 50 1.06 2.93 NIST_MME 1.01 2.89 0.351 #> 2 Uniform 50 1.06 2.93 NIST_MLE 1 3 0.333 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_uniform_stats_tbl","title":"Distribution Statistics — util_uniform_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_uniform_stats_tbl","text":"","code":"util_uniform_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_uniform_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_uniform_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_uniform_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_uniform_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_uniform_stats_tbl","text":"","code":"library(dplyr) tidy_uniform() %>% util_uniform_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 16 #> $ tidy_function \"tidy_uniform\" #> $ function_call \"Uniform c(0, 1)\" #> $ distribution \"Uniform\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.5 #> $ median 0.5 #> $ std_dv 0.2886751 #> $ coeff_var 0.5773503 #> $ skewness 0 #> $ kurtosis 1.8 #> $ computed_std_skew -0.1081732 #> $ computed_std_kurt 1.875426 #> $ ci_lo 0.05778033 #> $ ci_hi 0.9367315"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Weibull Parameters — util_weibull_param_estimate","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated weibull data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"","code":"util_weibull_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"function attempt estimate weibull shape scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_weibull(.shape = 1, .scale = 2)$y output <- util_weibull_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Weibull 50 0.0135 6.80 NIST 1.28 2.27 0.564 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_weibull_stats_tbl","title":"Distribution Statistics — util_weibull_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_weibull_stats_tbl","text":"","code":"util_weibull_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_weibull_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_weibull_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_weibull_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_weibull_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_weibull_stats_tbl","text":"","code":"library(dplyr) tidy_weibull() %>% util_weibull_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 16 #> $ tidy_function \"tidy_weibull\" #> $ function_call \"Weibull c(1, 1)\" #> $ distribution \"Weibull\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.8890894 #> $ median 0.5468908 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 0.961554 #> $ coeff_var 0.924586 #> $ computed_std_skew 0.8608088 #> $ computed_std_kurt 2.676956 #> $ ci_lo 0.04976536 #> $ ci_hi 2.665091"},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-development-version","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity (development version)","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-development-version","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity (development version)","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvments-development-version","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvments","title":"TidyDensity (development version)","text":"Fix #210 - Fix param_grid order internal affected attributes thus display order parameters. Fix #211 - Add High Low CI tidy_distribution_summary_tbl() Fix #213 - Use purrr::compact() list distributions passed order prevent issue occurring #212 Fix #212 - Make tidy_distribution_comparison() robust terms handling bad erroneous data. Fix #216 - Add attribute “tibble_type” tidy_multi_single_dist() helps work functions like tidy_random_walk()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-120","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.0","title":"TidyDensity 1.2.0","text":"CRAN release: 2022-06-08","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.0","text":"Fix #181 - Add functions color_blind() td_scale_fill_colorblind() td_scale_color_colorblind() Fix #187 - Add functions ci_lo() ci_hi() Fix #189 - Add function tidy_bootstrap() Fix #190 - Add function bootstrap_unnest_tbl() Fix #202 - Add function tidy_distribution_comparison()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-2-0","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.2.0","text":"Fix #176 - Update _autoplot functions include cumulative mean MCMC chart taking advantage .num_sims parameter tidy_ distribution functions. Fix #184 - Update tidy_empirical() add parameter .distribution_type Fix #183 - tidy_empirical() now plotted _autoplot functions. Fix #188 - Add .num_sims parameter tidy_empirical() Fix #196 - Add ci_lo() ci_hi() stats tbl functions. Fix #201 - Correct attribute distribution_family_type discrete tidy_geometric()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-110","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.1.0","title":"TidyDensity 1.1.0","text":"CRAN release: 2022-05-06","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-1-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.1.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-1-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.1.0","text":"Fix #119 - Add function tidy_four_autoplot() - auto plot density, qq, quantile probability plots single graph. Fix #125 - Add function util_weibull_param_estimate() Fix #126 - Add function util_uniform_param_estimate() Fix #127 - Add function util_cauchy_param_estimate() Fix #130 - Add function tidy_t() - Also add plotting functions. Fix #151 - Add function tidy_mixture_density() Fix #150 - Add function util_geometric_stats_tbl() Fix #149 - Add function util_hypergeometric_stats_tbl() Fix #148 - Add function util_logistic_stats_tbl() Fix #147 - Add function util_lognormal_stats_tbl() Fix #146 - Add function util_negative_binomial_stats_tbl() Fix #145 - Add function util_normal_stats_tbl() Fix #144 - Add function util_pareto_stats_tbl() Fix #143 - Add function util_poisson_stats_tbl() Fix #142 - Add function util_uniform_stats_tbl() Fix #141 - Add function util_cauchy_stats_tbl() Fix #140 - Add function util_t_stats_tbl() Fix #139 - Add function util_f_stats_tbl() Fix #138 - Add function util_chisquare_stats_tbl() Fix #137 - Add function util_weibull_stats_tbl() Fix #136 - Add function util_gamma_stats_tbl() Fix #135 - Add function util_exponential_stats_tbl() Fix #134 - Add function util_binomial_stats_tbl() Fix #133 - Add function util_beta_stats_tbl()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-1-0","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.1.0","text":"Fix #110 - Bug fix, correct p calculation tidy_poisson() now produce correct probability chart auto plot functions. Fix #112 - Bug fix, correct p calculation tidy_hypergeometric() produce correct probability chart auto plot functions. Fix #115 - Fix spelling Quantile chart. Fix #117 - Fix probability plot x axis label. Fix #118 - Fix fill color combined auto plot Fix #122 - tidy_distribution_summary_tbl() function take output tidy_multi_single_dist() Fix #166 - Change plotting functions ggplot2::xlim(0, max_dy) ggplot2::ylim(0, max_dy) Fix #169 - Fix computation q column Fix #170 - Fix graphing quantile chart due #169","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-101","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.0.1","title":"TidyDensity 1.0.1","text":"CRAN release: 2022-03-27","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-0-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.0.1","text":"Fix #91 - Bug fix, change tidy_gamma() parameter .rate .scale Fixtidy_autoplot_functions incorporate change. Fixutil_gamma_param_estimate()sayscaleinstead ofrate` returned estimated parameters.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-0-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.0.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-0-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.0.1","text":"Fix #90 - Make sure .geom_smooth set TRUE ggplot2::xlim(0, max_dy) set. Fix #100 - tidy_multi_single_dist() failed distribution single parameter like tidy_poisson() Fix #96 - Enhance tidy_ distribution functions add attribute either discrete continuous helps autoplot process. Fix #97 - Enhance tidy_autoplot() use histogram lines density plot depending distribution discrete continuous. Fix #99 - Enhance tidy_multi_dist_autoplot() use histogram lines density plot depending distribution discrete continuous.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-100","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.0.0","title":"TidyDensity 1.0.0","text":"CRAN release: 2022-03-08","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-0-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.0.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-0-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.0.0","text":"Fix #27 - Add function tidy_binomial() Fix #32 - Add function tidy_geometric() Fix #33 - Add function tidy_negative_binomial() Fix #34 - Add function tidy_zero_truncated_poisson() Fix #35 - Add function tidy_zero_truncated_geometric() Fix #36 - Add function tidy_zero_truncated_binomial() Fix #37 - Add function tidy_zero_truncated_negative_binomial() Fix #41 - Add function tidy_pareto1() Fix #42 - Add function tidy_pareto() Fix #43 - Add function tidy_inverse_pareto() Fix #58 - Add function tidy_random_walk() Fix #60 - Add function tidy_random_walk_autoplot() Fix #47 - Add function tidy_generalized_pareto() Fix #44 - Add function tidy_paralogistic() Fix #38 - Add function tidy_inverse_exponential() Fix #45 - Add function tidy_inverse_gamma() Fix #46 - Add function tidy_inverse_weibull() Fix #48 - Add function tidy_burr() Fix #49 - Add function tidy_inverse_burr() Fix #50 - Add function tidy_inverse_normal() Fix #51 - Add function tidy_generalized_beta() Fix #26 - Add function tidy_multi_single_dist() Fix #62 - Add function tidy_multi_dist_autoplot() Fix #66 - Add function tidy_combine_distributions() Fix #69 - Add functions tidy_kurtosis_vec(), tidy_skewness_vec(), tidy_range_statistic() Fix #75 - Add function util_beta_param_estimate() Fix #76 - Add function util_binomial_param_estimate() Fix #77 - Add function util_exponential_param_estimate() Fix #78 - Add function util_gamma_param_estimate() Fix #79 - Add function util_geometric_param_estimate() Fix #80 - Add function util_hypergeometric_param_estimate() Fix #81 - Add function util_lognormal_param_estimate() Fix #89 - Add function tidy_scale_zero_one_vec() Fix #87 - Add function tidy_combined_autoplot() Fix #82 - Add function util_logistic_param_estimate() Fix #83 - Add function util_negative_binomial_param_estimate() Fix #84 - Add function util_normal_param_estimate() Fix #85 - Add function util_pareto_param_estimate() Fix #86 - Add function util_poisson_param_estimate()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"fixes-and-minor-improvements-1-0-0","dir":"Changelog","previous_headings":"","what":"Fixes and Minor Improvements","title":"TidyDensity 1.0.0","text":"Fix #30 - Move crayon, rstudioapi, cli Suggests Imports due pillar longer importing. Fix #52 - Add parameter .geom_rug tidy_autoplot() function Fix #54 - Add parameter .geom_point tidy_autoplot() function Fix #53 - Add parameter .geom_smooth tidy_autoplot() function Fix #55 - Add parameter .geom_jitter tidy_autoplot() function Fix #57 - Fix tidy_autoplot() distribution tidy_empirical() legend argument fail. Fix #56 - Add attributes .n .num_sims (1L now) tidy_empirical() Fix #61 - Update _pkgdown.yml file update site. Fix #67 - Add param_grid, param_grid_txt, dist_with_params attributes tidy_ distribution functions. Fix #70 - Add ... grouping parameter tidy_distribution_summary_tbl() Fix #88 - Make column dist_type factor tidy_combine_distributions()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-001","dir":"Changelog","previous_headings":"","what":"TidyDensity 0.0.1","title":"TidyDensity 0.0.1","text":"CRAN release: 2022-01-21","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-0-0-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 0.0.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-0-0-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 0.0.1","text":"Fix #1 - Add function tidy_normal() Fix #4 - Add function tidy_gamma() Fix #5 - Add function tidy_beta() Fix #6 - Add function tidy_poisson() Fix #2 - Add function tidy_autoplot() Fix #11 - Add function tidy_distribution_summary_tbl() Fix #10 - Add function tidy_empirical() Fix #13 - Add function tidy_uniform() Fix #14 - Add function tidy_exponential() Fix #15 - Add function tidy_logistic() Fix #16 - Add function tidy_lognormal() Fix #17 - Add function tidy_weibull() Fix #18 - Add function tidy_chisquare() Fix #19 - Add function tidy_cauchy() Fix #20 - Add function tidy_hypergeometric() Fix #21 - Add function tidy_f()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-0-0-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 0.0.1","text":"None","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 0.0.0.9000","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 0.0.0.9000","text":"Added NEWS.md file track changes package.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"fixes-and-minor-improvements-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"Fixes and Minor Improvements","title":"TidyDensity 0.0.0.9000","text":"None","code":""}] +[{"path":"https://www.spsanderson.com/TidyDensity/articles/getting-started.html","id":"example","dir":"Articles","previous_headings":"","what":"Example","title":"Getting Started with TidyDensity","text":"basic example shows easy generate data TidyDensity: example plot tidy_normal data. can also take look plots number simulations greater nine. automatically turn legend become noisy.","code":"library(TidyDensity) library(dplyr) library(ggplot2) tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.812 -3.35 0.000228 0.5 0.343 #> 2 1 2 -0.950 -3.21 0.000641 0.508 -0.647 #> 3 1 3 -1.31 -3.06 0.00158 0.516 -0.903 #> 4 1 4 -0.306 -2.92 0.00343 0.524 -0.264 #> 5 1 5 1.16 -2.77 0.00661 0.533 0.551 #> 6 1 6 -0.314 -2.63 0.0114 0.541 -0.268 #> 7 1 7 -0.951 -2.48 0.0179 0.549 -0.647 #> 8 1 8 -0.795 -2.34 0.0261 0.557 -0.547 #> 9 1 9 2.53 -2.20 0.0367 0.565 Inf #> 10 1 10 -1.10 -2.05 0.0509 0.573 -0.746 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows tn <- tidy_normal(.n = 100, .num_sims = 6) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\") tn <- tidy_normal(.n = 100, .num_sims = 20) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Steven Sanderson. Author, maintainer. Steven Sanderson. Copyright holder.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Sanderson S (2022). TidyDensity: Functions Tidy Analysis Generation Random Data. R package version 1.2.0.9000, https://github.com/spsanderson/TidyDensity.","code":"@Manual{, title = {TidyDensity: Functions for Tidy Analysis and Generation of Random Data}, author = {Steven Sanderson}, year = {2022}, note = {R package version 1.2.0.9000}, url = {https://github.com/spsanderson/TidyDensity}, }"},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement spsanderson@gmail.com. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.0, available https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"tidydensity-","dir":"","previous_headings":"","what":"Functions for Tidy Analysis and Generation of Random Data","title":"Functions for Tidy Analysis and Generation of Random Data","text":"goal TidyDensity make working random numbers different distributions easy. tidy_ distribution functions provide following components: [r_] [d_] [q_] [p_]","code":""},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Functions for Tidy Analysis and Generation of Random Data","text":"can install released version TidyDensity CRAN : development version GitHub :","code":"install.packages(\"TidyDensity\") # install.packages(\"devtools\") devtools::install_github(\"spsanderson/TidyDensity\")"},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"example","dir":"","previous_headings":"","what":"Example","title":"Functions for Tidy Analysis and Generation of Random Data","text":"basic example shows solve common problem: example plot tidy_normal data. can also take look plots number simulations greater nine. automatically turn legend become noisy.","code":"library(TidyDensity) library(dplyr) library(ggplot2) tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.02 -3.45 0.000231 0.5 0.334 #> 2 1 2 0.807 -3.29 0.000697 0.508 0.229 #> 3 1 3 0.558 -3.14 0.00181 0.516 0.108 #> 4 1 4 -0.113 -2.98 0.00401 0.524 -0.216 #> 5 1 5 0.519 -2.83 0.00764 0.533 0.0890 #> 6 1 6 0.615 -2.68 0.0126 0.541 0.136 #> 7 1 7 -1.01 -2.52 0.0181 0.549 -0.698 #> 8 1 8 0.180 -2.37 0.0233 0.557 -0.0738 #> 9 1 9 0.0577 -2.21 0.0285 0.565 -0.133 #> 10 1 10 -1.09 -2.06 0.0354 0.573 -0.747 #> # … with 40 more rows tn <- tidy_normal(.n = 100, .num_sims = 6) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\") tn <- tidy_normal(.n = 100, .num_sims = 20) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2022 Steven Paul Sandeson II, MPH Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"Unnest data output tidy_bootstrap().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"","code":"bootstrap_unnest_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":".data data passed tidy_bootstrap() function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"function takes input output tidy_bootstrap() function returns two column tibble. columns sim_number y looks attribute comes using tidy_bootstrap() work unless data comes function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"","code":"tb <- tidy_bootstrap(.x = mtcars$mpg) bootstrap_unnest_tbl(tb) #> # A tibble: 50,000 × 2 #> sim_number y #> #> 1 1 22.8 #> 2 1 10.4 #> 3 1 24.4 #> 4 1 15.8 #> 5 1 30.4 #> 6 1 15 #> 7 1 15.2 #> 8 1 13.3 #> 9 1 21.4 #> 10 1 10.4 #> # … with 49,990 more rows #> # ℹ Use `print(n = ...)` to see more rows bootstrap_unnest_tbl(tb) %>% tidy_distribution_summary_tbl(sim_number) #> # A tibble: 2,000 × 13 #> sim_num…¹ mean_…² media…³ std_val min_val max_val skewn…⁴ kurto…⁵ range iqr #> #> 1 1 20.3 21.4 6.52 10.4 30.4 0.112 1.93 20 9.2 #> 2 2 18.9 19.2 5.00 10.4 30.4 0.316 2.61 20 6.8 #> 3 3 18.5 17.3 3.98 10.4 27.3 0.406 2.82 16.9 5.8 #> 4 4 20.4 19.2 4.99 15 33.9 1.12 3.70 18.9 7 #> 5 5 19.1 17.8 5.72 10.4 32.4 0.899 3.05 22 6.5 #> 6 6 21.5 21 5.91 14.3 33.9 0.875 2.80 19.6 5 #> 7 7 19.3 18.1 4.95 10.4 33.9 1.27 5.00 23.5 4.6 #> 8 8 20.0 16.4 6.71 13.3 33.9 0.838 2.31 20.6 7.8 #> 9 9 22.5 21 7.06 10.4 33.9 0.0584 2.01 23.5 9.2 #> 10 10 18.8 15.8 6.09 10.4 33.9 1.58 4.61 23.5 5.5 #> # … with 1,990 more rows, 3 more variables: variance , ci_low , #> # ci_high , and abbreviated variable names ¹​sim_number, ²​mean_val, #> # ³​median_val, ⁴​skewness, ⁵​kurtosis #> # ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":null,"dir":"Reference","previous_headings":"","what":"Confidence Interval Generic — ci_hi","title":"Confidence Interval Generic — ci_hi","text":"Gets upper 97.5% quantile numeric vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Confidence Interval Generic — ci_hi","text":"","code":"ci_hi(.x, .na_rm = FALSE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Confidence Interval Generic — ci_hi","text":".x vector numeric values .na_rm Boolean, defaults FALSE. Passed quantile function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Confidence Interval Generic — ci_hi","text":"numeric value.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Confidence Interval Generic — ci_hi","text":"Gets upper 97.5% quantile numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Confidence Interval Generic — ci_hi","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Confidence Interval Generic — ci_hi","text":"","code":"x <- mtcars$mpg ci_hi(x) #> [1] 32.7375"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":null,"dir":"Reference","previous_headings":"","what":"Confidence Interval Generic — ci_lo","title":"Confidence Interval Generic — ci_lo","text":"Gets lower 2.5% quantile numeric vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Confidence Interval Generic — ci_lo","text":"","code":"ci_lo(.x, .na_rm = FALSE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Confidence Interval Generic — ci_lo","text":".x vector numeric values .na_rm Boolean, defaults FALSE. Passed quantile function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Confidence Interval Generic — ci_lo","text":"numeric value.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Confidence Interval Generic — ci_lo","text":"Gets lower 2.5% quantile numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Confidence Interval Generic — ci_lo","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Confidence Interval Generic — ci_lo","text":"","code":"x <- mtcars$mpg ci_lo(x) #> [1] 10.4"},{"path":"https://www.spsanderson.com/TidyDensity/reference/color_blind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — color_blind","title":"Provide Colorblind Compliant Colors — color_blind","text":"8 Hex RGB color definitions suitable charts colorblind people.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/color_blind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — color_blind","text":"","code":"color_blind()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"Provide Colorblind Compliant Colors","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"","code":"td_scale_color_colorblind(..., theme = \"td\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"... Data passed function theme defaults td allowed value","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"Provide Colorblind Compliant Colors","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"","code":"td_scale_fill_colorblind(..., theme = \"td\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"... Data passed function theme defaults td allowed value","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidyeval.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy eval helpers — tidyeval","title":"Tidy eval helpers — tidyeval","text":"page lists tidy eval tools reexported package rlang. learn using tidy eval scripts packages high level, see dplyr programming vignette ggplot2 packages vignette. Metaprogramming section Advanced R may also useful deeper dive. tidy eval operators {{, !!, !!! syntactic constructs specially interpreted tidy eval functions. mostly need {{, !! !!! advanced operators use simple cases. curly-curly operator {{ allows tunnel data-variables passed function arguments inside tidy eval functions. {{ designed individual arguments. pass multiple arguments contained dots, use ... normal way. enquo() enquos() delay execution one several function arguments. former returns single expression, latter returns list expressions. defused, expressions longer evaluate . must injected back evaluation context !! (single expression) !!! (list expressions). simple case, code equivalent usage {{ ... . Defusing enquo() enquos() needed complex cases, instance need inspect modify expressions way. .data pronoun object represents current slice data. variable name string, use .data pronoun subset variable [[. Another tidy eval operator :=. makes possible use glue curly-curly syntax LHS =. technical reasons, R language support complex expressions left =, use := workaround. Many tidy eval functions like dplyr::mutate() dplyr::summarise() give automatic name unnamed inputs. need create sort automatic names , use as_label(). instance, glue-tunnelling syntax can reproduced manually : Expressions defused enquo() (tunnelled {{) need simple column names, can arbitrarily complex. as_label() handles cases gracefully. code assumes simple column name, use as_name() instead. safer throws error input name expected.","code":"my_function <- function(data, var, ...) { data %>% group_by(...) %>% summarise(mean = mean({{ var }})) } my_function <- function(data, var, ...) { # Defuse var <- enquo(var) dots <- enquos(...) # Inject data %>% group_by(!!!dots) %>% summarise(mean = mean(!!var)) } my_var <- \"disp\" mtcars %>% summarise(mean = mean(.data[[my_var]])) my_function <- function(data, var, suffix = \"foo\") { # Use `{{` to tunnel function arguments and the usual glue # operator `{` to interpolate plain strings. data %>% summarise(\"{{ var }}_mean_{suffix}\" := mean({{ var }})) } my_function <- function(data, var, suffix = \"foo\") { var <- enquo(var) prefix <- as_label(var) data %>% summarise(\"{prefix}_mean_{suffix}\" := mean(!!var)) }"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Density Data — tidy_autoplot","title":"Automatic Plot of Density Data — tidy_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq mcmc number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Density Data — tidy_autoplot","text":"","code":"tidy_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Density Data — tidy_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Density Data — tidy_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Density Data — tidy_autoplot","text":"function spit one following plots: density quantile probability qq mcmc","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Density Data — tidy_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Density Data — tidy_autoplot","text":"","code":"tidy_normal(.num_sims = 5) %>% tidy_autoplot() tidy_normal(.num_sims = 20) %>% tidy_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"function generate n random points beta distribution user provided, .shape1, .shape2, .ncp non-centrality parameter, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"","code":"tidy_beta(.n = 50, .shape1 = 1, .shape2 = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":".n number randomly generated points want. .shape1 non-negative parameter Beta distribution. .shape2 non-negative parameter Beta distribution. .ncp non-centrality parameter Beta distribution. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"function uses underlying stats::rbeta(), underlying p, d, q functions. information please see stats::rbeta()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"","code":"tidy_beta() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.418 -0.348 0.00182 0 0.417 #> 2 1 2 0.220 -0.313 0.00445 0.0204 0.218 #> 3 1 3 0.559 -0.279 0.00997 0.0408 0.558 #> 4 1 4 0.106 -0.244 0.0206 0.0612 0.103 #> 5 1 5 0.457 -0.209 0.0393 0.0816 0.456 #> 6 1 6 0.883 -0.175 0.0692 0.102 0.884 #> 7 1 7 0.723 -0.140 0.113 0.122 0.724 #> 8 1 8 0.733 -0.105 0.171 0.143 0.733 #> 9 1 9 0.799 -0.0708 0.240 0.163 0.799 #> 10 1 10 0.889 -0.0362 0.317 0.184 0.890 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"function generate n random points binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"","code":"tidy_binomial(.n = 50, .size = 0, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"function uses underlying stats::rbinom(), underlying p, d, q functions. information please see stats::rbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"","code":"tidy_binomial() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":null,"dir":"Reference","previous_headings":"","what":"Bootstrap Empirical Data — tidy_bootstrap","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"Takes input vector numeric data produces bootstrapped nested tibble simulation number.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"","code":"tidy_bootstrap( .x, .num_sims = 2000, .proportion = 0.8, .distribution_type = \"continuous\" )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bootstrap Empirical Data — tidy_bootstrap","text":".x vector data passed function. Must numeric vector. .num_sims default 2000, can set anything desired. warning pass console value less 2000. .proportion much original data want pass sampling function. default 0.80 (80%) .distribution_type can either 'continuous' 'discrete'","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"nested tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"function take numeric input vector produce tibble bootstrapped values list. table output two columns: sim_number bootstrap_samples sim_number corresponds many times want data resampled, bootstrap_samples column contains list boostrapped resampled data.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) #> # A tibble: 2,000 × 2 #> sim_number bootstrap_samples #> #> 1 1 #> 2 2 #> 3 3 #> 4 4 #> 5 5 #> 6 6 #> 7 7 #> 8 8 #> 9 9 #> 10 10 #> # … with 1,990 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"function generate n random points Burr distribution user provided, .shape1, .shape2, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"","code":"tidy_burr( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":".n number randomly generated points want. .shape1 Must strictly positive. .shape2 Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"function uses underlying actuar::rburr(), underlying p, d, q functions. information please see actuar::rburr()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"","code":"tidy_burr() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.515 -2.55 0.00118 0 0.0152 #> 2 1 2 3.61 -1.76 0.0143 0.0200 0.119 #> 3 1 3 9.87 -0.960 0.0768 0.0392 0.410 #> 4 1 4 0.771 -0.163 0.192 0.0577 0.0231 #> 5 1 5 0.329 0.633 0.245 0.0755 0.00962 #> 6 1 6 0.00644 1.43 0.196 0.0926 0 #> 7 1 7 2.39 2.23 0.139 0.109 0.0755 #> 8 1 8 4.19 3.02 0.105 0.125 0.141 #> 9 1 9 0.0584 3.82 0.0708 0.140 0.00153 #> 10 1 10 0.728 4.61 0.0319 0.155 0.0218 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"function generate n random points cauchy distribution user provided, .location, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"","code":"tidy_cauchy(.n = 50, .location = 0, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":".n number randomly generated points want. .location location parameter. .scale scale parameter, must greater equal 0. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"function uses underlying stats::rcauchy(), underlying p, d, q functions. information please see stats::rcauchy()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"","code":"tidy_cauchy() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 -245. -246. 6.25e- 4 0.5 -Inf #> 2 1 2 -1.85 -241. 1.93e-13 0.506 3.48 #> 3 1 3 -6.74 -235. 4.13e-19 0.513 2.85 #> 4 1 4 -1.23 -230. 0 0.519 3.58 #> 5 1 5 -0.856 -224. 1.90e-19 0.526 3.64 #> 6 1 6 0.364 -219. 2.58e-19 0.532 3.86 #> 7 1 7 4.09 -213. 1.72e-20 0.539 4.70 #> 8 1 8 0.109 -208. 3.83e-18 0.545 3.81 #> 9 1 9 -0.289 -202. 3.38e-19 0.552 3.74 #> 10 1 10 5.12 -197. 0 0.558 5.00 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"function generate n random points chisquare distribution user provided, .df, .ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"","code":"tidy_chisquare(.n = 50, .df = 1, .ncp = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":".n number randomly generated points want. .df Degrees freedom (non-negative can non-integer) .ncp Non-centrality parameter, must non-negative. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"function uses underlying stats::rchisq(), underlying p, d, q functions. information please see stats::rchisq()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"","code":"tidy_chisquare() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0533 -3.27 0.00104 0 0.0000986 #> 2 1 2 0.505 -2.91 0.00278 0.0691 0.00887 #> 3 1 3 0.0252 -2.55 0.00668 0.0978 0.0000220 #> 4 1 4 9.09 -2.19 0.0145 0.120 3.69 #> 5 1 5 0.817 -1.83 0.0283 0.138 0.0232 #> 6 1 6 0.178 -1.47 0.0499 0.155 0.00110 #> 7 1 7 0.0126 -1.11 0.0797 0.169 0.00000550 #> 8 1 8 5.78 -0.751 0.116 0.183 1.21 #> 9 1 9 11.1 -0.391 0.152 0.195 Inf #> 10 1 10 3.14 -0.0315 0.183 0.207 0.343 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"","code":"tidy_combined_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":".data data passed function tidy_multi_dist() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"","code":"combined_tbl <- tidy_combine_distributions( tidy_normal(), tidy_gamma(), tidy_beta() ) combined_tbl #> # A tibble: 150 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 -0.386 -4.69 0.000177 0.5 -0.0743 Gaussian c(0, 1) #> 2 1 2 -1.74 -4.51 0.000490 0.508 -0.698 Gaussian c(0, 1) #> 3 1 3 -0.475 -4.33 0.00119 0.516 -0.112 Gaussian c(0, 1) #> 4 1 4 -1.55 -4.14 0.00253 0.524 -0.603 Gaussian c(0, 1) #> 5 1 5 -1.39 -3.96 0.00473 0.533 -0.521 Gaussian c(0, 1) #> 6 1 6 0.989 -3.78 0.00778 0.541 0.531 Gaussian c(0, 1) #> 7 1 7 -0.0218 -3.60 0.0113 0.549 0.0800 Gaussian c(0, 1) #> 8 1 8 -1.71 -3.41 0.0145 0.557 -0.684 Gaussian c(0, 1) #> 9 1 9 -1.23 -3.23 0.0167 0.565 -0.445 Gaussian c(0, 1) #> 10 1 10 0.611 -3.05 0.0183 0.573 0.355 Gaussian c(0, 1) #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows combined_tbl %>% tidy_combined_autoplot() combined_tbl %>% tidy_combined_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":null,"dir":"Reference","previous_headings":"","what":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"allows user specify n number tidy_ distributions can combined single tibble. preferred method combining multiple distributions different types, example Gaussian distribution Beta distribution. generates single tibble added column dist_type give distribution family name associated parameters.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"","code":"tidy_combine_distributions(...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"... ... can place different distributions","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"Allows user generate tibble different tidy_ distributions","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"","code":"tn <- tidy_normal() tb <- tidy_beta() tc <- tidy_cauchy() tidy_combine_distributions(tn, tb, tc) #> # A tibble: 150 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 0.0440 -3.56 0.000287 0.5 0.139 Gaussian c(0, 1) #> 2 1 2 -1.06 -3.42 0.000771 0.508 -0.529 Gaussian c(0, 1) #> 3 1 3 0.643 -3.29 0.00186 0.516 0.509 Gaussian c(0, 1) #> 4 1 4 -0.319 -3.15 0.00404 0.524 -0.0734 Gaussian c(0, 1) #> 5 1 5 -0.174 -3.01 0.00789 0.533 0.0115 Gaussian c(0, 1) #> 6 1 6 0.399 -2.87 0.0140 0.541 0.353 Gaussian c(0, 1) #> 7 1 7 0.659 -2.74 0.0225 0.549 0.520 Gaussian c(0, 1) #> 8 1 8 0.373 -2.60 0.0335 0.557 0.337 Gaussian c(0, 1) #> 9 1 9 -2.34 -2.46 0.0465 0.565 -Inf Gaussian c(0, 1) #> 10 1 10 -1.52 -2.32 0.0615 0.573 -0.871 Gaussian c(0, 1) #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows ## OR tidy_combine_distributions( tidy_normal(), tidy_beta(), tidy_cauchy(), tidy_logistic() ) #> # A tibble: 200 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 0.153 -3.28 0.000244 0.5 0.182 Gaussian c(0, 1) #> 2 1 2 -0.897 -3.15 0.000637 0.508 -0.504 Gaussian c(0, 1) #> 3 1 3 0.461 -3.03 0.00151 0.516 0.385 Gaussian c(0, 1) #> 4 1 4 0.0108 -2.90 0.00327 0.524 0.0912 Gaussian c(0, 1) #> 5 1 5 0.0208 -2.77 0.00650 0.533 0.0975 Gaussian c(0, 1) #> 6 1 6 -1.36 -2.64 0.0120 0.541 -0.876 Gaussian c(0, 1) #> 7 1 7 0.360 -2.51 0.0206 0.549 0.317 Gaussian c(0, 1) #> 8 1 8 -1.67 -2.38 0.0336 0.557 -1.22 Gaussian c(0, 1) #> 9 1 9 0.554 -2.25 0.0520 0.565 0.450 Gaussian c(0, 1) #> 10 1 10 -1.40 -2.13 0.0768 0.573 -0.918 Gaussian c(0, 1) #> # … with 190 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Compare Empirical Data to Distributions — tidy_distribution_comparison","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"Compare empirical data set different distributions help find distribution best fit.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"","code":"tidy_distribution_comparison(.x, .distribution_type = \"continuous\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":".x data set passed function .distribution_type kind data , can one continuous discrete","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"invisible list object. tibble printed.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"purpose function take data set provided try find distribution may fit best. parameter .distribution_type must set either continuous discrete order function try appropriate types distributions. following distributions used: Continuous: tidy_beta tidy_cauchy tidy_exponential tidy_gamma tidy_logistic tidy_lognormal tidy_pareto tidy_uniform tidy_weibull Discrete: tidy_binomial tidy_geometric tidy_hypergeometric tidy_poisson","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"","code":"xc <- mtcars$mpg tidy_distribution_comparison(xc, \"continuous\") #> For the beta distribution, its mean 'mu' should be 0 < mu < 1. The data will #> therefore be scaled to enforce this. #> # A tibble: 9 × 2 #> dist_with_params abs_tot_deviance #> #> 1 Beta c(1.11, 1.58, 0) 0.0880 #> 2 Uniform c(8.34, 31.84) 1.18 #> 3 Weibull c(3.58, 22.29) 1.43 #> 4 Cauchy c(19.2, 7.38) 1.79 #> 5 Lognormal c(2.96, 0.29) 2.76 #> 6 Exponential c(0.05) 3.09 #> 7 Gamma c(11.47, 1.75) 3.20 #> 8 Logistic c(20.09, 3.27) 6.47 #> 9 Pareto c(10.4, 1.62) 6.64 xd <- trunc(xc) tidy_distribution_comparison(xd, \"discrete\") #> # A tibble: 4 × 2 #> dist_with_params abs_tot_deviance #> #> 1 Hypergeometric c(21, 11, 21) 0.978 #> 2 Geometric c(0.05) 1.72 #> 3 Binomial c(32, 0.03) 2.81 #> 4 Poisson c(19.69) 6.86"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"function returns summary statistics tibble. use y column tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"","code":"tidy_distribution_summary_tbl(.data, ...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":".data data going passed tidy_ distribution function. ... grouping variable gets passed dplyr::group_by() dplyr::select().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"summary stats tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"function takes tidy_ distribution table return tibble following information: sim_number mean_val median_val std_val min_val max_val skewness kurtosis range iqr variance kurtosis skewness come package healthyR.ai","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"","code":"library(dplyr) #> #> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union tn <- tidy_normal(.num_sims = 5) tb <- tidy_beta(.num_sims = 5) tidy_distribution_summary_tbl(tn) #> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> #> 1 -0.0300 -0.0569 0.939 -2.77 2.54 0.0167 2.65 5.32 1.36 0.881 #> # … with 2 more variables: ci_low , ci_high , and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance #> # ℹ Use `colnames()` to see all variable names tidy_distribution_summary_tbl(tn, sim_number) #> # A tibble: 5 × 13 #> sim_number mean_…¹ media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> #> 1 1 -0.0470 -0.210 0.880 -1.46 2.54 0.651 3.16 4.00 1.13 #> 2 2 0.0211 0.0589 0.876 -2.09 1.85 -0.117 2.39 3.94 1.46 #> 3 3 -0.0889 -0.117 0.978 -2.77 1.91 -0.168 3.11 4.68 1.34 #> 4 4 -0.0121 -0.0495 0.945 -1.47 2.00 0.244 1.99 3.47 1.51 #> 5 5 -0.0231 0.203 1.04 -2.30 1.93 -0.287 2.43 4.23 1.42 #> # … with 3 more variables: variance , ci_low , ci_high , and #> # abbreviated variable names ¹​mean_val, ²​median_val, ³​skewness, ⁴​kurtosis #> # ℹ Use `colnames()` to see all variable names data_tbl <- tidy_combine_distributions(tn, tb) tidy_distribution_summary_tbl(data_tbl) #> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> #> 1 0.235 0.352 0.742 -2.77 2.54 -0.758 4.05 5.32 0.766 0.551 #> # … with 2 more variables: ci_low , ci_high , and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance #> # ℹ Use `colnames()` to see all variable names tidy_distribution_summary_tbl(data_tbl, dist_type) #> # A tibble: 2 × 13 #> dist_type mean_…¹ media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> #> 1 Gaussian… -0.0300 -0.0569 0.939 -2.77 2.54 0.0167 2.65 5.32 1.36 #> 2 Beta c(1… 0.500 0.497 0.286 0.00391 1.00 0.0366 1.83 0.996 0.483 #> # … with 3 more variables: variance , ci_low , ci_high , and #> # abbreviated variable names ¹​mean_val, ²​median_val, ³​skewness, ⁴​kurtosis #> # ℹ Use `colnames()` to see all variable names"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Empirical — tidy_empirical","title":"Tidy Empirical — tidy_empirical","text":"function takes single argument .x vector return tibble information similar tidy_ distribution functions. y column set equal dy density function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Empirical — tidy_empirical","text":"","code":"tidy_empirical(.x, .num_sims = 1, .distribution_type = \"continuous\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Empirical — tidy_empirical","text":".x vector numbers .num_sims many simulations run, defaults 1. .distribution_type string either \"continuous\" \"discrete\". function default \"continuous\"","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Empirical — tidy_empirical","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Empirical — tidy_empirical","text":"function takes single argument .x vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Empirical — tidy_empirical","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Empirical — tidy_empirical","text":"","code":"x <- mtcars$mpg tidy_empirical(.x = x, .distribution_type = \"continuous\") #> # A tibble: 32 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 21 2.97 0.000114 0.625 10.4 #> 2 1 2 21 4.21 0.000455 0.625 10.4 #> 3 1 3 22.8 5.44 0.00142 0.781 13.3 #> 4 1 4 21.4 6.68 0.00355 0.688 14.3 #> 5 1 5 18.7 7.92 0.00721 0.469 14.7 #> 6 1 6 18.1 9.16 0.0124 0.438 15 #> 7 1 7 14.3 10.4 0.0192 0.125 15.2 #> 8 1 8 24.4 11.6 0.0281 0.812 15.2 #> 9 1 9 22.8 12.9 0.0395 0.781 15.5 #> 10 1 10 19.2 14.1 0.0516 0.531 15.8 #> # … with 22 more rows #> # ℹ Use `print(n = ...)` to see more rows tidy_empirical(.x = x, .num_sims = 10, .distribution_type = \"continuous\") #> # A tibble: 320 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 10.4 3.80 0.000128 0.0625 10.4 #> 2 1 2 21.4 4.98 0.000554 0.688 10.4 #> 3 1 3 19.2 6.17 0.00182 0.531 14.3 #> 4 1 4 15.2 7.35 0.00453 0.25 14.3 #> 5 1 5 32.4 8.54 0.00889 0.969 14.7 #> 6 1 6 30.4 9.72 0.0147 0.938 14.7 #> 7 1 7 14.7 10.9 0.0229 0.156 15.2 #> 8 1 8 22.8 12.1 0.0362 0.781 15.2 #> 9 1 9 21.4 13.3 0.0551 0.688 15.2 #> 10 1 10 16.4 14.5 0.0737 0.344 15.2 #> # … with 310 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"function generate n random points exponential distribution user provided, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"","code":"tidy_exponential(.n = 50, .rate = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":".n number randomly generated points want. .rate vector rates .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"function uses underlying stats::rexp(), underlying p, d, q functions. information please see stats::rexp()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"","code":"tidy_exponential() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.465 -1.14 0.00160 0 0.0858 #> 2 1 2 0.545 -0.979 0.00578 0.0202 0.101 #> 3 1 3 0.468 -0.817 0.0175 0.0400 0.0864 #> 4 1 4 0.0529 -0.655 0.0453 0.0594 0.00917 #> 5 1 5 0.326 -0.494 0.0993 0.0784 0.0594 #> 6 1 6 3.90 -0.332 0.186 0.0970 1.18 #> 7 1 7 0.0343 -0.170 0.299 0.115 0.00584 #> 8 1 8 1.11 -0.00882 0.417 0.133 0.218 #> 9 1 9 2.11 0.153 0.507 0.151 0.467 #> 10 1 10 1.61 0.314 0.543 0.168 0.336 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated F Distribution Tibble — tidy_f","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"function generate n random points rf distribution user provided, df1,df2, ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"","code":"tidy_f(.n = 50, .df1 = 1, .df2 = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":".n number randomly generated points want. .df1 Degrees freedom, Inf allowed. .df2 Degrees freedom, Inf allowed. .ncp Non-centrality parameter. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"function uses underlying stats::rf(), underlying p, d, q functions. information please see stats::rf()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"","code":"tidy_f() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0000562 -2.28 2.84e- 3 0 0 #> 2 1 2 0.460 3.05 6.62e- 2 0.0903 7.94e- 6 #> 3 1 3 0.163 8.37 9.38e- 3 0.127 1.00e- 6 #> 4 1 4 3.92 13.7 1.55e- 3 0.154 5.76e- 4 #> 5 1 5 0.00199 19.0 1.11e- 2 0.177 1.40e-10 #> 6 1 6 0.0288 24.4 9.22e- 3 0.197 3.10e- 8 #> 7 1 7 0.0114 29.7 8.77e-11 0.214 4.81e- 9 #> 8 1 8 0.526 35.0 0 0.230 1.04e- 5 #> 9 1 9 1.29 40.3 8.03e-19 0.244 6.20e- 5 #> 10 1 10 103. 45.7 1.51e-18 0.258 5.34e- 1 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Density Data — tidy_four_autoplot","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"","code":"tidy_four_autoplot( .data, .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"","code":"tidy_normal(.num_sims = 5) %>% tidy_four_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"function generate n random points gamma distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"","code":"tidy_gamma(.n = 50, .shape = 1, .scale = 0.3, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":".n number randomly generated points want. .shape strictly 0 infinity. .scale standard deviation randomly generated data. strictly 0 infinity. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"function uses underlying stats::rgamma(), underlying p, d, q functions. information please see stats::rgamma()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"","code":"tidy_gamma() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0134 -0.295 0.00458 0 0 #> 2 1 2 0.0482 -0.243 0.0204 0.0658 0.00539 #> 3 1 3 0.160 -0.190 0.0715 0.127 0.0235 #> 4 1 4 0.106 -0.138 0.198 0.185 0.0147 #> 5 1 5 0.505 -0.0857 0.442 0.238 0.0872 #> 6 1 6 0.125 -0.0333 0.800 0.288 0.0177 #> 7 1 7 0.601 0.0191 1.20 0.335 0.108 #> 8 1 8 0.466 0.0715 1.55 0.379 0.0792 #> 9 1 9 0.0363 0.124 1.74 0.420 0.00353 #> 10 1 10 0.0461 0.176 1.77 0.458 0.00508 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"function generate n random points generalized beta distribution user provided, .shape1, .shape2, .shape3, .rate, /.sclae, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"","code":"tidy_generalized_beta( .n = 50, .shape1 = 1, .shape2 = 1, .shape3 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":".n number randomly generated points want. .shape1 non-negative parameter Beta distribution. .shape2 non-negative parameter Beta distribution. .shape3 non-negative parameter Beta distribution. .rate alternative way specify .scale parameter. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"function uses underlying stats::rbeta(), underlying p, d, q functions. information please see stats::rbeta()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"","code":"tidy_generalized_beta() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.300 -0.350 0.00285 0 0.293 #> 2 1 2 0.638 -0.315 0.00675 0.0204 0.635 #> 3 1 3 0.603 -0.280 0.0147 0.0408 0.600 #> 4 1 4 0.656 -0.245 0.0295 0.0612 0.652 #> 5 1 5 0.688 -0.210 0.0547 0.0816 0.685 #> 6 1 6 0.895 -0.175 0.0933 0.102 0.895 #> 7 1 7 0.509 -0.140 0.147 0.122 0.504 #> 8 1 8 0.0368 -0.106 0.214 0.143 0.0272 #> 9 1 9 1.00 -0.0706 0.289 0.163 1 #> 10 1 10 0.599 -0.0358 0.364 0.184 0.595 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"function generate n random points generalized Pareto distribution user provided, .shape1, .shape2, .rate .scale number #' random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"","code":"tidy_generalized_pareto( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":".n number randomly generated points want. .shape1 Must positive. .shape2 Must positive. .rate alternative way specify .scale argument .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"function uses underlying actuar::rgenpareto(), underlying p, d, q functions. information please see actuar::rgenpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"","code":"tidy_generalized_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2.31 -2.57 0.000800 0 0.0478 #> 2 1 2 1.46 -1.46 0.0240 0.02 0.0294 #> 3 1 3 2.68 -0.341 0.160 0.0392 0.0561 #> 4 1 4 1.61 0.776 0.266 0.0577 0.0325 #> 5 1 5 0.456 1.89 0.152 0.0755 0.00822 #> 6 1 6 0.158 3.01 0.0821 0.0926 0.00213 #> 7 1 7 0.884 4.13 0.0468 0.109 0.0171 #> 8 1 8 0.691 5.24 0.0258 0.125 0.0131 #> 9 1 9 0.333 6.36 0.0264 0.140 0.00569 #> 10 1 10 3.07 7.48 0.0223 0.155 0.0648 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"function generate n random points geometric distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"","code":"tidy_geometric(.n = 50, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":".n number randomly generated points want. .prob probability success trial 0 < prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"function uses underlying stats::rgeom(), underlying p, d, q functions. information please see stats::rgeom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"","code":"tidy_geometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"function generate n random points hypergeometric distribution user provided, m,nn, k, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"","code":"tidy_hypergeometric(.n = 50, .m = 0, .nn = 0, .k = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":".n number randomly generated points want. .m number white balls urn .nn number black balls urn .k number balls drawn fro urn. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"function uses underlying stats::rhyper(), underlying p, d, q functions. information please see stats::rhyper()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"","code":"tidy_hypergeometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"function generate n random points Inverse Burr distribution user provided, .shape1, .shape2, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"","code":"tidy_inverse_burr( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":".n number randomly generated points want. .shape1 Must strictly positive. .shape2 Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"function uses underlying actuar::rinvburr(), underlying p, d, q functions. information please see actuar::rinvburr()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"","code":"tidy_inverse_burr() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.396 -0.999 4.51e- 3 0 0.00233 #> 2 1 2 0.439 2.34 4.96e- 2 0.02 0.00260 #> 3 1 3 1.01 5.68 3.15e- 2 0.0392 0.00615 #> 4 1 4 22.9 9.03 1.79e- 2 0.0577 0.165 #> 5 1 5 0.311 12.4 0 0.0755 0.00180 #> 6 1 6 0.831 15.7 6.77e-18 0.0926 0.00504 #> 7 1 7 0.817 19.1 2.00e- 2 0.109 0.00495 #> 8 1 8 19.1 22.4 9.65e- 3 0.125 0.133 #> 9 1 9 1.15 25.7 1.39e-15 0.140 0.00704 #> 10 1 10 2.13 29.1 0 0.155 0.0132 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"function generate n random points inverse exponential distribution user provided, .rate .scale number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"","code":"tidy_inverse_exponential(.n = 50, .rate = 1, .scale = 1/.rate, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":".n number randomly generated points want. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"function uses underlying actuar::rinvexp(), underlying p, d, q functions. information please see actuar::rinvexp()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"","code":"tidy_inverse_exponential() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.640 -1.28 0.000613 0 0.193 #> 2 1 2 1.02 0.306 0.277 5.24e-22 0.221 #> 3 1 3 0.333 1.90 0.213 2.29e-11 0.155 #> 4 1 4 9.10 3.48 0.0163 8.06e- 8 0.469 #> 5 1 5 4.71 5.07 0.0188 4.79e- 6 0.355 #> 6 1 6 0.507 6.66 0.0224 5.55e- 5 0.180 #> 7 1 7 0.759 8.25 0.0221 2.84e- 4 0.203 #> 8 1 8 0.671 9.84 0.00577 9.12e- 4 0.196 #> 9 1 9 0.467 11.4 0.0162 2.19e- 3 0.175 #> 10 1 10 1.42 13.0 0.0130 4.32e- 3 0.242 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"function generate n random points inverse gamma distribution user provided, .shape, .rate, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"","code":"tidy_inverse_gamma( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"function uses underlying actuar::rinvgamma(), underlying p, d, q functions. information please see actuar::rinvgamma()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"","code":"tidy_inverse_gamma() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.500 -1.12 0.000570 0 0.219 #> 2 1 2 0.650 -0.323 0.0648 5.24e-22 0.236 #> 3 1 3 2.28 0.473 0.406 2.29e-11 0.354 #> 4 1 4 3.01 1.27 0.330 8.06e- 8 0.394 #> 5 1 5 0.494 2.06 0.207 4.79e- 6 0.218 #> 6 1 6 2.43 2.86 0.0660 5.55e- 5 0.362 #> 7 1 7 0.682 3.66 0.0153 2.84e- 4 0.240 #> 8 1 8 4.79 4.45 0.0476 9.12e- 4 0.486 #> 9 1 9 0.772 5.25 0.0231 2.19e- 3 0.248 #> 10 1 10 0.802 6.04 0.0197 4.32e- 3 0.251 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"function generate n random points Inverse Gaussian distribution user provided, .mean, .shape, .dispersionThe function returns tibble simulation number column x column corresponds n randomly generated points. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"","code":"tidy_inverse_normal( .n = 50, .mean = 1, .shape = 1, .dispersion = 1/.shape, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":".n number randomly generated points want. .mean Must strictly positive. .shape Must strictly positive. .dispersion alternative way specify .shape. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"function uses underlying actuar::rinvgauss(). information please see rinvgauss()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"","code":"tidy_inverse_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.668 -0.786 0.00129 0 0.223 #> 2 1 2 0.828 -0.614 0.00743 6.89e-12 0.247 #> 3 1 3 0.193 -0.442 0.0314 1.98e- 6 0.130 #> 4 1 4 1.55 -0.270 0.0975 1.40e- 4 0.348 #> 5 1 5 0.208 -0.0982 0.227 1.22e- 3 0.134 #> 6 1 6 1.30 0.0738 0.404 4.54e- 3 0.314 #> 7 1 7 0.301 0.246 0.572 1.10e- 2 0.158 #> 8 1 8 0.267 0.418 0.672 2.09e- 2 0.150 #> 9 1 9 0.811 0.590 0.681 3.39e- 2 0.244 #> 10 1 10 0.887 0.762 0.609 4.96e- 2 0.255 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"function generate n random points inverse pareto distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"","code":"tidy_inverse_pareto(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":".n number randomly generated points want. .shape Must positive. .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"function uses underlying actuar::rinvpareto(), underlying p, d, q functions. information please see actuar::rinvpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"","code":"tidy_inverse_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.104 -1.98 0.00148 0 0.00579 #> 2 1 2 0.267 -1.55 0.00932 0.02 0.0156 #> 3 1 3 1.27 -1.13 0.0400 0.0392 0.0807 #> 4 1 4 0.0695 -0.701 0.117 0.0577 0.00375 #> 5 1 5 0.138 -0.275 0.236 0.0755 0.00786 #> 6 1 6 1.15 0.152 0.339 0.0926 0.0723 #> 7 1 7 0.00630 0.578 0.357 0.109 0 #> 8 1 8 16.9 1.00 0.292 0.125 Inf #> 9 1 9 0.691 1.43 0.198 0.140 0.0421 #> 10 1 10 0.529 1.86 0.126 0.155 0.0319 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"function generate n random points weibull distribution user provided, .shape, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"","code":"tidy_inverse_weibull( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"function uses underlying actuar::rinvweibull(), underlying p, d, q functions. information please see actuar::rinvweibull()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"","code":"tidy_inverse_weibull() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.14 -3.12 0.000592 0 0.230 #> 2 1 2 0.721 -1.44 0.0289 5.24e-22 0.203 #> 3 1 3 0.833 0.240 0.177 2.29e-11 0.211 #> 4 1 4 26.6 1.92 0.168 8.06e- 8 0.952 #> 5 1 5 0.926 3.60 0.0604 4.79e- 6 0.217 #> 6 1 6 3.77 5.28 0.0205 5.55e- 5 0.328 #> 7 1 7 1.41 6.96 0.0151 2.84e- 4 0.243 #> 8 1 8 6.73 8.64 0.0130 9.12e- 4 0.409 #> 9 1 9 0.415 10.3 0.00792 2.19e- 3 0.175 #> 10 1 10 19.0 12.0 0.00720 4.32e- 3 0.720 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"function takes vector input return kurtosis vector. length vector must least four numbers. kurtosis explains sharpness peak distribution data. ((1/n) * sum(x - mu})^4) / ((()1/n) * sum(x - mu)^2)^2","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"","code":"tidy_kurtosis_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":".x numeric vector length four .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"kurtosis vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"function return kurtosis vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"","code":"tidy_kurtosis_vec(rnorm(100, 3, 2)) #> [1] 2.804531"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"function generate n random points logistic distribution user provided, .location, .scale, number random simulations produced. function returns tibble simulation number column x column corresonds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"","code":"tidy_logistic(.n = 50, .location = 0, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":".n number randomly generated points want. .location location parameter .scale scale parameter .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"function uses underlying stats::rlogis(), underlying p, d, q functions. information please see stats::rlogis()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"","code":"tidy_logistic() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 -3.49 -7.60 0.000164 0.5 -1.02 #> 2 1 2 0.105 -7.34 0.000605 0.505 0.616 #> 3 1 3 0.614 -7.09 0.00178 0.510 0.866 #> 4 1 4 -0.514 -6.83 0.00422 0.515 0.335 #> 5 1 5 2.75 -6.57 0.00809 0.520 2.62 #> 6 1 6 1.35 -6.31 0.0127 0.525 1.28 #> 7 1 7 1.94 -6.06 0.0167 0.531 1.70 #> 8 1 8 -1.29 -5.80 0.0194 0.536 -0.000432 #> 9 1 9 0.368 -5.54 0.0215 0.541 0.742 #> 10 1 10 -4.97 -5.28 0.0241 0.546 -2.13 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"function generate n random points lognormal distribution user provided, .meanlog, .sdlog, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"","code":"tidy_lognormal(.n = 50, .meanlog = 0, .sdlog = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":".n number randomly generated points want. .meanlog Mean distribution log scale default 0 .sdlog Standard deviation distribution log scale default 1 .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"function uses underlying stats::rlnorm(), underlying p, d, q functions. information please see stats::rlnorm()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"","code":"tidy_lognormal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.806 -0.803 0.00136 0 0.186 #> 2 1 2 1.98 -0.477 0.0223 0.0000497 0.324 #> 3 1 3 2.21 -0.151 0.147 0.000690 0.349 #> 4 1 4 0.861 0.174 0.419 0.00261 0.193 #> 5 1 5 0.559 0.500 0.586 0.00611 0.149 #> 6 1 6 1.70 0.826 0.514 0.0112 0.293 #> 7 1 7 1.02 1.15 0.386 0.0179 0.214 #> 8 1 8 0.323 1.48 0.276 0.0258 0.104 #> 9 1 9 1.24 1.80 0.213 0.0350 0.241 #> 10 1 10 1.37 2.13 0.155 0.0451 0.255 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Mixture Data — tidy_mixture_density","title":"Tidy Mixture Data — tidy_mixture_density","text":"Create mixture model data resulting density line plots.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Mixture Data — tidy_mixture_density","text":"","code":"tidy_mixture_density(...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Mixture Data — tidy_mixture_density","text":"... random data want pass. Example rnorm(50,0,1) something like tidy_normal(.mean = 5, .sd = 1)","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Mixture Data — tidy_mixture_density","text":"list object","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Mixture Data — tidy_mixture_density","text":"function allows make mixture model data. allows produce density data plots data strictly one family one single type distribution given set parameters. example function allow mix say tidy_normal(.mean = 0, .sd = 1) tidy_normal(.mean = 5, .sd = 1) can mix match distributions. output list object three components. Data input_data (random data passed) dist_tbl (tibble passed random data) density_tbl (tibble x y data stats::density()) Plots line_plot - Plots dist_tbl dens_plot - Plots density_tbl Input Functions input_fns - list functions parameters passed function itsefl","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Mixture Data — tidy_mixture_density","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Mixture Data — tidy_mixture_density","text":"","code":"output <- tidy_mixture_density(rnorm(100, 0, 1), tidy_normal(.mean = 5, .sd = 1)) output$data #> $dist_tbl #> # A tibble: 150 × 2 #> x y #> #> 1 1 0.333 #> 2 2 -0.0511 #> 3 3 -1.03 #> 4 4 0.509 #> 5 5 -0.851 #> 6 6 0.172 #> 7 7 -0.879 #> 8 8 -0.624 #> 9 9 -0.634 #> 10 10 0.279 #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows #> #> $dens_tbl #> # A tibble: 150 × 2 #> x y #> #> 1 -4.64 0.0000573 #> 2 -4.53 0.0000843 #> 3 -4.43 0.000123 #> 4 -4.33 0.000178 #> 5 -4.23 0.000254 #> 6 -4.13 0.000358 #> 7 -4.03 0.000499 #> 8 -3.93 0.000689 #> 9 -3.83 0.000941 #> 10 -3.73 0.00127 #> # … with 140 more rows #> # ℹ Use `print(n = ...)` to see more rows #> #> $input_data #> $input_data$`rnorm(100, 0, 1)` #> [1] 0.33342619 -0.05114829 -1.02589077 0.50859412 -0.85105505 0.17182496 #> [7] -0.87928216 -0.62423926 -0.63372190 0.27889474 -0.11626197 0.42019549 #> [13] 1.47728634 -1.66744786 -0.63121170 0.97293952 -1.56802951 -1.02692720 #> [19] -0.69669962 0.34314491 1.15491887 0.57761782 -0.68948748 0.46592641 #> [25] 0.25631436 0.93835509 1.04507292 0.58419675 0.44774433 0.86763206 #> [31] -1.38716640 0.90247322 0.03802568 -0.19743450 -0.15585718 0.44554174 #> [37] -0.25509400 0.61735913 0.20086887 1.80765909 -0.41911107 0.21932587 #> [43] 0.37960628 -0.61274732 0.80434732 -0.60182400 1.02822689 0.05834868 #> [49] -1.64055387 -0.05372774 0.65242186 -0.44600212 -1.39207561 0.04146409 #> [55] 0.08912960 -0.36027981 0.06137096 -1.06299889 0.38376279 -1.31024859 #> [61] -0.68134020 -0.57123343 0.61758079 1.06798590 0.90954557 0.58497673 #> [67] 0.45474176 0.14015397 -0.08640400 -0.18171620 -1.13990898 0.31030059 #> [73] -0.29217276 0.71135816 -0.71979306 0.75314480 -0.06201897 -0.09067604 #> [79] 0.99650669 -2.14289116 -0.03136940 -0.73987854 -0.11989643 -0.98127744 #> [85] -0.29344371 1.14717591 0.55248378 -1.18758624 0.92007779 0.51273282 #> [91] 1.74964419 -0.50026369 2.05555196 -0.76483125 0.53089638 1.07722257 #> [97] 0.02716953 2.20322460 0.45217447 -0.63219571 #> #> $input_data$`tidy_normal(.mean = 5, .sd = 1)` #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 5.78 0.803 0.000280 0.000000287 5.36 #> 2 1 2 6.39 0.972 0.000874 0.000000319 5.67 #> 3 1 3 6.00 1.14 0.00234 0.000000354 5.47 #> 4 1 4 5.18 1.31 0.00538 0.000000393 5.09 #> 5 1 5 4.44 1.48 0.0107 0.000000436 4.77 #> 6 1 6 5.71 1.65 0.0182 0.000000484 5.33 #> 7 1 7 3.92 1.82 0.0267 0.000000537 4.53 #> 8 1 8 3.76 1.99 0.0339 0.000000595 4.45 #> 9 1 9 5.87 2.16 0.0374 0.000000660 5.41 #> 10 1 10 5.62 2.33 0.0368 0.000000731 5.29 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows #> #> output$plots #> $line_plot #> #> $dens_plot #> output$input_fns #> [[1]] #> rnorm(100, 0, 1) #> #> [[2]] #> tidy_normal(.mean = 5, .sd = 1) #>"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"","code":"tidy_multi_dist_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":".data data passed function tidy_multi_dist() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"","code":"tn <- tidy_multi_single_dist( .tidy_dist = \"tidy_normal\", .param_list = list( .n = 500, .mean = c(-2, 0, 2), .sd = 1, .num_sims = 5 ) ) tn %>% tidy_multi_dist_autoplot() tn %>% tidy_multi_dist_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Generate multiple distributions data tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"","code":"tidy_multi_single_dist(.tidy_dist = NULL, .param_list = list())"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":".tidy_dist type tidy_ distribution want run. can choose one. .param_list must list() object parameters want pass TidyDensity tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Generate multiple distributions data tidy_ distribution function. allows simulate multiple distributions family order view shapes change parameter changes. can visualize differences however choose.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"","code":"tidy_multi_single_dist( .tidy_dist = \"tidy_normal\", .param_list = list( .n = 50, .mean = c(-1, 0, 1), .sd = 1, .num_sims = 3 ) ) #> # A tibble: 450 × 8 #> sim_number dist_name x y dx dy p q #> #> 1 1 Gaussian c(-1, 1) 1 -0.929 -4.23 0.000432 0.841 -1.09 #> 2 1 Gaussian c(-1, 1) 2 0.116 -4.09 0.00126 0.846 -0.499 #> 3 1 Gaussian c(-1, 1) 3 -0.545 -3.95 0.00325 0.851 -0.880 #> 4 1 Gaussian c(-1, 1) 4 -1.01 -3.81 0.00742 0.856 -1.14 #> 5 1 Gaussian c(-1, 1) 5 -2.54 -3.67 0.0151 0.860 -2.21 #> 6 1 Gaussian c(-1, 1) 6 0.513 -3.52 0.0273 0.865 -0.234 #> 7 1 Gaussian c(-1, 1) 7 -0.992 -3.38 0.0441 0.869 -1.13 #> 8 1 Gaussian c(-1, 1) 8 0.467 -3.24 0.0643 0.873 -0.267 #> 9 1 Gaussian c(-1, 1) 9 -0.274 -3.10 0.0851 0.878 -0.729 #> 10 1 Gaussian c(-1, 1) 10 -0.619 -2.96 0.103 0.882 -0.921 #> # … with 440 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"function generate n random points negative binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"","code":"tidy_negative_binomial(.n = 50, .size = 1, .prob = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":".n number randomly generated points want. .size target number successful trials, dispersion parameter (shape parameter gamma mixing distribution). Must strictly positive, need integer. .prob Probability success trial 0 < .prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"function uses underlying stats::rnbinom(), underlying p, d, q functions. information please see stats::rnbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"","code":"tidy_negative_binomial() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2 -8.98 0.000155 0.1 0 #> 2 1 2 2 -7.56 0.000633 0.1 0 #> 3 1 3 7 -6.13 0.00210 0.1 1 #> 4 1 4 0 -4.70 0.00568 0.1 0 #> 5 1 5 28 -3.27 0.0126 0.1 7 #> 6 1 6 20 -1.84 0.0234 0.1 4 #> 7 1 7 6 -0.416 0.0365 0.1 1 #> 8 1 8 8 1.01 0.0487 0.1 1 #> 9 1 9 8 2.44 0.0569 0.1 1 #> 10 1 10 18 3.87 0.0592 0.1 4 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"function generate n random points Gaussian distribution user provided, .mean, .sd - standard deviation number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, dnorm, pnorm qnorm data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"","code":"tidy_normal(.n = 50, .mean = 0, .sd = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":".n number randomly generated points want. .mean mean randomly generated data. .sd standard deviation randomly generated data. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"function uses underlying stats::rnorm(), stats::pnorm(), stats::qnorm() functions generate data given parameters. information please see stats::rnorm()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"","code":"tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.12 -3.76 0.000250 0.5 0.651 #> 2 1 2 -0.436 -3.61 0.000787 0.508 -0.156 #> 3 1 3 0.867 -3.46 0.00210 0.516 0.504 #> 4 1 4 -0.934 -3.31 0.00472 0.524 -0.410 #> 5 1 5 0.696 -3.16 0.00898 0.533 0.411 #> 6 1 6 0.119 -3.01 0.0145 0.541 0.117 #> 7 1 7 -1.37 -2.87 0.0199 0.549 -0.655 #> 8 1 8 -1.02 -2.72 0.0237 0.557 -0.458 #> 9 1 9 -0.693 -2.57 0.0251 0.565 -0.285 #> 10 1 10 -0.482 -2.42 0.0252 0.573 -0.179 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"function generate n random points paralogistic distribution user provided, .shape, .rate, .scale number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"","code":"tidy_paralogistic( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"function uses underlying actuar::rparalogis(), underlying p, d, q functions. information please see actuar::rparalogis()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"","code":"tidy_paralogistic() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.284 -2.48 0.00117 0 0.00216 #> 2 1 2 2.48 0.247 0.269 0.0200 0.0196 #> 3 1 3 0.576 2.97 0.0576 0.0392 0.00446 #> 4 1 4 0.729 5.69 0.0115 0.0577 0.00566 #> 5 1 5 0.00643 8.41 0.0000119 0.0755 0 #> 6 1 6 0.415 11.1 0.00800 0.0926 0.00320 #> 7 1 7 0.0787 13.9 0.00274 0.109 0.000563 #> 8 1 8 0.308 16.6 0.00306 0.125 0.00236 #> 9 1 9 3.45 19.3 0.00781 0.140 0.0276 #> 10 1 10 1.30 22.0 0.00000630 0.155 0.0102 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"function generate n random points pareto distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"","code":"tidy_pareto(.n = 50, .shape = 10, .scale = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":".n number randomly generated points want. .shape Must positive. .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"function uses underlying actuar::rpareto(), underlying p, d, q functions. information please see actuar::rpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"","code":"tidy_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.00551 -0.00675 0.223 0 0.000998 #> 2 1 2 0.00464 -0.00533 1.30 0.844 0.000825 #> 3 1 3 0.000599 -0.00390 5.35 0.967 0.0000675 #> 4 1 4 0.000542 -0.00247 15.7 0.992 0.0000574 #> 5 1 5 0.00868 -0.00104 33.4 0.997 0.00165 #> 6 1 6 0.00682 0.000384 53.5 0.999 0.00126 #> 7 1 7 0.00541 0.00181 67.6 1.00 0.000977 #> 8 1 8 0.00421 0.00324 72.1 1.00 0.000742 #> 9 1 9 0.00484 0.00467 69.9 1.00 0.000865 #> 10 1 10 0.00425 0.00609 64.7 1.00 0.000750 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"function generate n random points single parameter pareto distribution user provided, .shape, .min, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"","code":"tidy_pareto1(.n = 50, .shape = 1, .min = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":".n number randomly generated points want. .shape Must positive. .min lower bound support distribution. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"function uses underlying actuar::rpareto1(), underlying p, d, q functions. information please see actuar::rpareto1()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"","code":"tidy_pareto1() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.81 -4.26 0.000920 0 1.00 #> 2 1 2 1.51 2.38 0.133 0 1.00 #> 3 1 3 2.80 9.02 0.0102 0 1.01 #> 4 1 4 20.2 15.7 0.0111 0 1.06 #> 5 1 5 1.03 22.3 0.00672 0 1 #> 6 1 6 1.10 28.9 0.0000308 0 1.00 #> 7 1 7 1.25 35.6 0.00428 0 1.00 #> 8 1 8 13.2 42.2 0.00186 0 1.04 #> 9 1 9 1.69 48.8 0.0000000158 0 1.00 #> 10 1 10 1.46 55.5 0 0 1.00 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"function generate n random points Poisson distribution user provided, .lambda, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"","code":"tidy_poisson(.n = 50, .lambda = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":".n number randomly generated points want. .lambda vector non-negative means. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"function uses underlying stats::rpois(), underlying p, d, q functions. information please see stats::rpois()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"","code":"tidy_poisson() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 -1.34 0.00400 0.368 0 #> 2 1 2 1 -1.21 0.00952 0.368 0 #> 3 1 3 0 -1.07 0.0206 0.368 0 #> 4 1 4 2 -0.933 0.0408 0.368 1 #> 5 1 5 1 -0.797 0.0734 0.368 0 #> 6 1 6 0 -0.660 0.121 0.368 0 #> 7 1 7 1 -0.524 0.181 0.368 0 #> 8 1 8 1 -0.387 0.248 0.368 0 #> 9 1 9 1 -0.251 0.310 0.368 0 #> 10 1 10 0 -0.115 0.357 0.368 0 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Random Walk — tidy_random_walk","title":"Tidy Random Walk — tidy_random_walk","text":"Takes data tidy_ distribution function applies random walk calculation either cum_prod cum_sum y.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Random Walk — tidy_random_walk","text":"","code":"tidy_random_walk( .data, .initial_value = 0, .sample = FALSE, .replace = FALSE, .value_type = \"cum_prod\" )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Random Walk — tidy_random_walk","text":".data data passed tidy_ distribution function. .initial_value default 0, can set whatever want. .sample boolean value TRUE/FALSE. default FALSE. set TRUE y value tidy_ distribution function sampled. .replace boolean value TRUE/FALSE. default FALSE. set TRUE .sample set TRUE replace parameter sample function set TRUE. .value_type can take one three different values now. following: \"cum_prod\" - take cumprod y \"cum_sum\" - take cumsum y","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Random Walk — tidy_random_walk","text":"ungrouped tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Random Walk — tidy_random_walk","text":"Monte Carlo simulations first formally designed 1940’s developing nuclear weapons, since heavily used various fields use randomness solve problems potentially deterministic nature. finance, Monte Carlo simulations can useful tool give sense assets certain characteristics might behave future. complex sophisticated financial forecasting methods ARIMA (Auto-Regressive Integrated Moving Average) GARCH (Generalised Auto-Regressive Conditional Heteroskedasticity) attempt model randomness underlying macro factors seasonality volatility clustering, Monte Carlo random walks work surprisingly well illustrating market volatility long results taken seriously.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Random Walk — tidy_random_walk","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Random Walk — tidy_random_walk","text":"","code":"tidy_normal(.sd = .1, .num_sims = 25) %>% tidy_random_walk() #> # A tibble: 1,250 × 8 #> sim_number x y dx dy p q random_walk_value #> #> 1 1 1 0.0110 -0.389 0.00194 0.5 0.0106 0.0110 #> 2 1 2 0.151 -0.374 0.00495 0.581 0.0976 0.164 #> 3 1 3 0.0593 -0.358 0.0115 0.658 0.0368 0.233 #> 4 1 4 0.225 -0.343 0.0240 0.730 0.234 0.510 #> 5 1 5 -0.114 -0.327 0.0458 0.793 -0.0585 0.337 #> 6 1 6 -0.171 -0.312 0.0803 0.846 -0.0988 0.109 #> 7 1 7 -0.114 -0.296 0.131 0.890 -0.0584 -0.0179 #> 8 1 8 0.00830 -0.281 0.201 0.923 0.00919 -0.00977 #> 9 1 9 0.0477 -0.265 0.295 0.949 0.0303 0.0374 #> 10 1 10 0.0606 -0.250 0.421 0.967 0.0375 0.100 #> # … with 1,240 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"auto-plotting function take tidy_ distribution function arguments regard output visualization. number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"","code":"tidy_random_walk_autoplot( .data, .line_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .line_size size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"function produce simple random walk plot tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"","code":"tidy_normal(.sd = .1, .num_sims = 5) %>% tidy_random_walk(.value_type = \"cum_sum\") %>% tidy_random_walk_autoplot() tidy_normal(.sd = .1, .num_sims = 20) %>% tidy_random_walk(.value_type = \"cum_sum\", .sample = TRUE, .replace = TRUE) %>% tidy_random_walk_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the range statistic — tidy_range_statistic","title":"Get the range statistic — tidy_range_statistic","text":"Takes numeric vector returns back range vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the range statistic — tidy_range_statistic","text":"","code":"tidy_range_statistic(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the range statistic — tidy_range_statistic","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the range statistic — tidy_range_statistic","text":"single number, range statistic","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the range statistic — tidy_range_statistic","text":"Takes numeric vector returns range vector using diff range functions.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get the range statistic — tidy_range_statistic","text":"Steven P. Sandeson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the range statistic — tidy_range_statistic","text":"","code":"tidy_range_statistic(seq(1:10)) #> [1] 9"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Takes numeric vector return vector scaled [0,1]","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"","code":"tidy_scale_zero_one_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":".x numeric vector scaled [0,1] inclusive.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Takes numeric vector return vector scaled [0,1] input vector must numeric. computation fairly straightforward. may helpful trying compare distributions data distribution like beta requires data 0 1 $$y[h] = (x - min(x))/(max(x) - min(x))$$","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"","code":"vec_1 <- rnorm(100, 2, 1) vec_2 <- tidy_scale_zero_one_vec(vec_1) dens_1 <- density(vec_1) dens_2 <- density(vec_2) max_x <- max(dens_1$x, dens_2$x) max_y <- max(dens_1$y, dens_2$y) plot(dens_1, asp = max_y/max_x, main = \"Density vec_1 (Red) and vec_2 (Blue)\", col = \"red\", xlab = \"\", ylab = \"Density of Vec 1 and Vec 2\") lines(dens_2, col = \"blue\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Skewness of a Vector — tidy_skewness_vec","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"function takes vector input return skewness vector. length vector must least four numbers. skewness explains 'tailedness' distribution data. ((1/n) * sum(x - mu})^3) / ((()1/n) * sum(x - mu)^2)^(3/2)","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"","code":"tidy_skewness_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":".x numeric vector length four .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"skewness vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"function return skewness vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"","code":"tidy_skewness_vec(rnorm(100, 3, 2)) #> [1] -0.08732319"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated T Distribution Tibble — tidy_t","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"function generate n random points rt distribution user provided, df, ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"","code":"tidy_t(.n = 50, .df = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":".n number randomly generated points want. .df Degrees freedom, Inf allowed. .ncp Non-centrality parameter. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"function uses underlying stats::rt(), underlying p, d, q functions. information please see stats::rt()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"","code":"tidy_t() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.226 -22.5 2.86e- 3 0.5 -13.9 #> 2 1 2 1.11 -3.65 3.41e- 2 0.506 -13.3 #> 3 1 3 -0.167 15.2 9.01e-14 0.513 -14.2 #> 4 1 4 0.323 34.0 5.49e- 3 0.519 -13.8 #> 5 1 5 -0.00455 52.9 0 0.526 -14.0 #> 6 1 6 -2.69 71.7 0 0.532 -16.1 #> 7 1 7 7.74 90.6 2.73e-18 0.539 -10.2 #> 8 1 8 -0.358 109. 2.88e-20 0.545 -14.3 #> 9 1 9 0.866 128. 0 0.552 -13.5 #> 10 1 10 0.141 147. 2.64e-19 0.558 -14.0 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"function generate n random points uniform distribution user provided, .min .max values, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"","code":"tidy_uniform(.n = 50, .min = 0, .max = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":".n number randomly generated points want. .min lower limit distribution. .max upper limit distribution .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"function uses underlying stats::runif(), underlying p, d, q functions. information please see stats::runif()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"","code":"tidy_uniform() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0539 -0.377 0.00168 0 0.0517 #> 2 1 2 0.982 -0.341 0.00404 0.0204 0.996 #> 3 1 3 0.854 -0.306 0.00899 0.0408 0.866 #> 4 1 4 0.903 -0.270 0.0187 0.0612 0.916 #> 5 1 5 0.477 -0.235 0.0361 0.0816 0.483 #> 6 1 6 0.151 -0.199 0.0652 0.102 0.150 #> 7 1 7 0.368 -0.163 0.110 0.122 0.371 #> 8 1 8 0.367 -0.128 0.174 0.143 0.371 #> 9 1 9 0.202 -0.0923 0.258 0.163 0.202 #> 10 1 10 0.00306 -0.0568 0.359 0.184 0 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"function generate n random points weibull distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"","code":"tidy_weibull(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":".n number randomly generated points want. .shape Shape parameter defaults 0. .scale Scale parameter defaults 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"function uses underlying stats::rweibull(), underlying p, d, q functions. information please see stats::rweibull()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"","code":"tidy_weibull() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.223 -1.13 0.00121 0 0.0675 #> 2 1 2 0.245 -1.02 0.00315 0.0202 0.0745 #> 3 1 3 0.289 -0.902 0.00747 0.0400 0.0886 #> 4 1 4 0.0587 -0.787 0.0163 0.0594 0.0170 #> 5 1 5 0.539 -0.671 0.0326 0.0784 0.173 #> 6 1 6 0.00145 -0.556 0.0600 0.0970 0 #> 7 1 7 1.02 -0.440 0.102 0.115 0.357 #> 8 1 8 0.315 -0.325 0.159 0.133 0.0970 #> 9 1 9 0.223 -0.209 0.231 0.151 0.0675 #> 10 1 10 0.512 -0.0934 0.310 0.168 0.163 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"function generate n random points zero truncated binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"","code":"tidy_zero_truncated_binomial(.n = 50, .size = 0, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial 0 <= prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"function uses underlying actuar::rztbinom(), underlying p, d, q functions. information please see actuar::rztbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"","code":"tidy_zero_truncated_binomial() #> Warning: NaNs produced #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 NaN NaN #> 2 1 2 0 -1.18 0.0156 NaN NaN #> 3 1 3 0 -1.13 0.0220 NaN NaN #> 4 1 4 0 -1.08 0.0305 NaN NaN #> 5 1 5 0 -1.03 0.0418 NaN NaN #> 6 1 6 0 -0.983 0.0564 NaN NaN #> 7 1 7 0 -0.932 0.0749 NaN NaN #> 8 1 8 0 -0.882 0.0981 NaN NaN #> 9 1 9 0 -0.832 0.126 NaN NaN #> 10 1 10 0 -0.781 0.161 NaN NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"function generate n random points zero truncated Geometric distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"","code":"tidy_zero_truncated_geometric(.n = 50, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":".n number randomly generated points want. .prob probability success trial 0 < prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"function uses underlying actuar::rztgeom(), underlying p, d, q functions. information please see actuar::rztgeom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"","code":"tidy_zero_truncated_geometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 -0.235 0.0109 0 NaN #> 2 1 2 1 -0.184 0.0156 0 NaN #> 3 1 3 1 -0.134 0.0220 0 NaN #> 4 1 4 1 -0.0835 0.0305 0 NaN #> 5 1 5 1 -0.0331 0.0418 0 NaN #> 6 1 6 1 0.0173 0.0564 0 NaN #> 7 1 7 1 0.0677 0.0749 0 NaN #> 8 1 8 1 0.118 0.0981 0 NaN #> 9 1 9 1 0.168 0.126 0 NaN #> 10 1 10 1 0.219 0.161 0 NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"function generate n random points zero truncated binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"","code":"tidy_zero_truncated_negative_binomial( .n = 50, .size = 0, .prob = 1, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial 0 <= prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"function uses underlying actuar::rztnbinom(), underlying p, d, q functions. information please see actuar::rztnbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"","code":"tidy_zero_truncated_binomial() #> Warning: NaNs produced #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 NaN NaN #> 2 1 2 0 -1.18 0.0156 NaN NaN #> 3 1 3 0 -1.13 0.0220 NaN NaN #> 4 1 4 0 -1.08 0.0305 NaN NaN #> 5 1 5 0 -1.03 0.0418 NaN NaN #> 6 1 6 0 -0.983 0.0564 NaN NaN #> 7 1 7 0 -0.932 0.0749 NaN NaN #> 8 1 8 0 -0.882 0.0981 NaN NaN #> 9 1 9 0 -0.832 0.126 NaN NaN #> 10 1 10 0 -0.781 0.161 NaN NaN #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"function generate n random points Zero Truncated Poisson distribution user provided, .lambda, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"","code":"tidy_zero_truncated_poisson(.n = 50, .lambda = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":".n number randomly generated points want. .lambda vector non-negative means. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"function uses underlying actuar::rztpois(), underlying p, d, q functions. information please see actuar::rztpois()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"","code":"tidy_zero_truncated_poisson() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 0.0786 0.00875 0 1 #> 2 1 2 1 0.177 0.0218 0 1 #> 3 1 3 2 0.276 0.0489 0 1 #> 4 1 4 2 0.375 0.0989 0 1 #> 5 1 5 2 0.474 0.180 0 1 #> 6 1 6 3 0.573 0.297 0 2 #> 7 1 7 1 0.672 0.441 0 1 #> 8 1 8 2 0.770 0.590 0 1 #> 9 1 9 1 0.869 0.712 0 1 #> 10 1 10 1 0.968 0.776 0 1 #> # … with 40 more rows #> # ℹ Use `print(n = ...)` to see more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Beta Parameters — util_beta_param_estimate","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"function automatically scale data 0 1 already. means can pass vector like mtcars$mpg worry . function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated beta data. Three different methods shape parameters supplied: Bayes NIST mme EnvStats mme, see EnvStats::ebeta()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"","code":"util_beta_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Beta Parameters — util_beta_param_estimate","text":".x vector data passed function. Must numeric, values must 0 <= x <= 1 .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"function attempt estimate beta shape1 shape2 parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_beta_param_estimate(x) #> For the beta distribution, its mean 'mu' should be 0 < mu < 1. The data will #> therefore be scaled to enforce this. output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> #> 1 Beta 32 10.4 33.9 0.412 0.0658 Bayes 13.2 18.8 0.702 #> 2 Beta 32 10.4 33.9 0.412 0.0658 NIST_MME 1.11 1.58 0.702 #> 3 Beta 32 10.4 33.9 0.412 0.0658 EnvStats… 1.16 1.65 0.702 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() tb <- rbeta(50, 2.5, 1.4) util_beta_param_estimate(tb)$parameter_tbl #> There was no need to scale the data. #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> #> 1 Beta 50 0.190 0.997 0.675 0.0523 Bayes 33.7 16.3 2.07 #> 2 Beta 50 0.190 0.997 0.675 0.0523 NIST_MME 2.16 1.04 2.07 #> 3 Beta 50 0.190 0.997 0.675 0.0523 EnvStats… 2.22 1.07 2.07 #> # … with abbreviated variable name ¹​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_beta_stats_tbl","title":"Distribution Statistics — util_beta_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_beta_stats_tbl","text":"","code":"util_beta_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_beta_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_beta_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_beta_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_beta_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_beta_stats_tbl","text":"","code":"library(dplyr) tidy_beta() %>% util_beta_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_beta\" #> $ function_call \"Beta c(1, 1, 0)\" #> $ distribution \"Beta\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.5 #> $ mode \"undefined\" #> $ range \"0 to 1\" #> $ std_dv 0.2886751 #> $ coeff_var 0.5773503 #> $ skewness 0 #> $ kurtosis NA #> $ computed_std_skew 0.2541739 #> $ computed_std_kurt 2.124569 #> $ ci_lo 0.01215601 #> $ ci_hi 0.9050219"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Binomial Parameters — util_binomial_param_estimate","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"function check see given vector .x either numeric vector factor vector least two levels cause error function abort. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated binomial data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"","code":"util_binomial_param_estimate(.x, .size = NULL, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":".x vector data passed function. Must numeric, values must 0 <= x <= 1 .size Number trials, zero . .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"function attempt estimate binomial p_hat size parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tb <- rbinom(50, 1, .1) output <- util_binomial_param_estimate(tb) output$parameter_tbl #> # A tibble: 1 × 10 #> dist_type samp_size min max mean variance method prob size shape…¹ #> #> 1 Binomial 50 0 1 0.12 0.108 EnvStats_M… 0.12 50 0.0024 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_binomial_stats_tbl","title":"Distribution Statistics — util_binomial_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_binomial_stats_tbl","text":"","code":"util_binomial_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_binomial_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_binomial_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_binomial_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_binomial_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_binomial_stats_tbl","text":"","code":"library(dplyr) tidy_binomial() %>% util_binomial_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_binomial\" #> $ function_call \"Binomial c(0, 1)\" #> $ distribution \"Binomial\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode_lower 0 #> $ mode_upper 1 #> $ range \"0 to 0\" #> $ std_dv 0 #> $ coeff_var NaN #> $ skewness -Inf #> $ kurtosis NaN #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Cauchy Parameters — util_cauchy_param_estimate","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated cauchy data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"","code":"util_cauchy_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"function attempt estimate cauchy location scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_cauchy(.location = 0, .scale = 1)$y output <- util_cauchy_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max method location scale ratio #> #> 1 Cauchy 50 -20.3 5.93 MASS -0.0909 1.35 -0.0673 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_cauchy_stats_tbl","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"","code":"util_cauchy_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_cauchy_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"","code":"library(dplyr) tidy_cauchy() %>% util_cauchy_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_cauchy\" #> $ function_call \"Cauchy c(0, 1)\" #> $ distribution \"Cauchy\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean \"undefined\" #> $ median 0 #> $ mode 0 #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness 0 #> $ kurtosis \"undefined\" #> $ computed_std_skew 2.361671 #> $ computed_std_kurt 19.553 #> $ ci_lo -14.59186 #> $ ci_hi 4.52635"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_chisquare_stats_tbl","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"","code":"util_chisquare_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_chisquare_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"","code":"library(dplyr) tidy_chisquare() %>% util_chisquare_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_chisquare\" #> $ function_call \"Chisquare c(1, 1)\" #> $ distribution \"Chisquare\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ median 0.3333333 #> $ mode \"undefined\" #> $ std_dv 1.414214 #> $ coeff_var 1.414214 #> $ skewness 2.828427 #> $ kurtosis 15 #> $ computed_std_skew 1.369179 #> $ computed_std_kurt 4.203692 #> $ ci_lo 0.001979251 #> $ ci_hi 8.331546"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Exponential Parameters — util_exponential_param_estimate","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"function attempt estimate exponential rate parameter given vector values. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated exponential data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"","code":"util_exponential_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":".x vector data passed function. Must numeric. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"function see given vector .x numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"","code":"library(dplyr) library(ggplot2) te <- tidy_exponential(.rate = .1) %>% pull(y) output <- util_exponential_param_estimate(te) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max mean variance method rate #> #> 1 Exponential 50 0.199 38.2 10.9 83.1 NIST_MME 0.0916 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_exponential_stats_tbl","title":"Distribution Statistics — util_exponential_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_exponential_stats_tbl","text":"","code":"util_exponential_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_exponential_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_exponential_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_exponential_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_exponential_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_exponential_stats_tbl","text":"","code":"library(dplyr) tidy_exponential() %>% util_exponential_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_exponential\" #> $ function_call \"Exponential c(1)\" #> $ distribution \"Exponential\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ median 0.6931472 #> $ mode 1 #> $ range \"1 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 2 #> $ kurtosis 9 #> $ computed_std_skew 1.606079 #> $ computed_std_kurt 5.649964 #> $ ci_lo 0.03998032 #> $ ci_hi 2.62225"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_f_stats_tbl","title":"Distribution Statistics — util_f_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_f_stats_tbl","text":"","code":"util_f_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_f_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_f_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_f_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_f_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_f_stats_tbl","text":"","code":"library(dplyr) tidy_f() %>% util_f_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_f\" #> $ function_call \"F Distribution c(1, 1, 0)\" #> $ distribution \"F\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean \"undefined\" #> $ median \"Not computed\" #> $ mode \"undefined\" #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness \"undefined\" #> $ kurtosis \"Not computed\" #> $ computed_std_skew 6.333812 #> $ computed_std_kurt 42.96724 #> $ ci_lo 0.004044745 #> $ ci_hi 184.3791"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Gamma Parameters — util_gamma_param_estimate","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"function attempt estimate gamma shape scale parameters given vector values. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated gamma data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"","code":"util_gamma_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":".x vector data passed function. Must numeric. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"function see given vector .x numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tg <- tidy_gamma(.shape = 1, .scale = .3) %>% pull(y) output <- util_gamma_param_estimate(tg) output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape scale shape…¹ #> #> 1 Gamma 50 0.00446 1.58 0.335 0.316 NIST_MME 1.12 0.299 3.74 #> 2 Gamma 50 0.00446 1.58 0.335 0.316 EnvStats… 1.10 0.299 3.67 #> 3 Gamma 50 0.00446 1.58 0.335 0.316 EnvStats… 1.07 0.299 3.56 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_gamma_stats_tbl","title":"Distribution Statistics — util_gamma_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_gamma_stats_tbl","text":"","code":"util_gamma_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_gamma_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_gamma_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_gamma_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_gamma_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_gamma_stats_tbl","text":"","code":"library(dplyr) tidy_gamma() %>% util_gamma_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_gamma\" #> $ function_call \"Gamma c(1, 0.3)\" #> $ distribution \"Gamma\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 2 #> $ kurtosis 9 #> $ computed_std_skew 2.522683 #> $ computed_std_kurt 11.60953 #> $ ci_lo 0.01712874 #> $ ci_hi 1.022674"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Geometric Parameters — util_geometric_param_estimate","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"function attempt estimate geometric prob parameter given vector values .x. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated geometric data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"","code":"util_geometric_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":".x vector data passed function. Must non-negative integers. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"function see given vector .x numeric vector. attempt estimate prob parameter geometric distribution.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tg <- tidy_geometric(.prob = .1) %>% pull(y) output <- util_geometric_param_estimate(tg) output$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean variance sum_x method shape #> #> 1 Geometric 50 0 30 6.76 40.4 338 EnvStats_MME 0.129 #> 2 Geometric 50 0 30 6.76 40.4 338 EnvStats_MVUE 0.127 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_geometric_stats_tbl","title":"Distribution Statistics — util_geometric_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_geometric_stats_tbl","text":"","code":"util_geometric_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_geometric_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_geometric_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_geometric_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_geometric_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_geometric_stats_tbl","text":"","code":"library(dplyr) tidy_geometric() %>% util_geometric_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_geometric\" #> $ function_call \"Geometric c(1)\" #> $ distribution \"Geometric\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 0 #> $ coeff_var 0 #> $ skewness Inf #> $ kurtosis Inf #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"function attempt estimate geometric prob parameter given vector values .x. Estimate m, number white balls urn, m+n, total number balls urn, hypergeometric distribution.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"","code":"util_hypergeometric_param_estimate( .x, .m = NULL, .total = NULL, .k, .auto_gen_empirical = TRUE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":".x non-negative integer indicating number white balls sample size .k drawn without replacement urn. missing, undefined infinite values. .m Non-negative integer indicating number white balls urn. must supply .m .total, . missing values. .total positive integer indicating total number balls urn (.e., m+n). must supply .m .total, . missing values. .k positive integer indicating number balls drawn without replacement urn. missing values. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"function see given vector .x numeric integer. attempt estimate prob parameter geometric distribution. Missing (NA), undefined (NaN), infinite (Inf, -Inf) values allowed. Let .x observation hypergeometric distribution parameters .m = M, .n = N, .k = K. R nomenclature, .x represents number white balls drawn sample .k balls drawn without replacement urn containing .m white balls .n black balls. total number balls urn thus .m + .n. Denote total number balls T = .m + .n","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"","code":"library(dplyr) library(ggplot2) th <- rhyper(10, 20, 30, 5) output <- util_hypergeometric_param_estimate(th, .total = 50, .k = 5) output$parameter_tbl #> # A tibble: 2 × 5 #> dist_type samp_size method m total #> #> 1 Hypergeometric 10 EnvStats_MLE 20.4 NA #> 2 Hypergeometric 10 EnvStats_MVUE 20 50 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_hypergeometric_stats_tbl","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"","code":"util_hypergeometric_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"","code":"library(dplyr) tidy_hypergeometric() %>% util_hypergeometric_stats_tbl() %>% glimpse() #> Warning: NaNs produced #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_hypergeometric\" #> $ function_call \"Hypergeometric c(0, 0, 0)\" #> $ distribution \"Hypergeometric\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean NaN #> $ mode_lower -0.5 #> $ mode_upper 0.5 #> $ range \"0 to Inf\" #> $ std_dv NaN #> $ coeff_var NaN #> $ skewness NaN #> $ kurtosis NaN #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Logistic Parameters — util_logistic_param_estimate","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated logistic data. Three different methods shape parameters supplied: MLE MME MMUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"","code":"util_logistic_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"function attempt estimate logistic location scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_logistic_param_estimate(x) output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> #> 1 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 3.27 6.14 #> 2 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 3.32 6.05 #> 3 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 12.6 1.60 #> # … with abbreviated variable names ¹​location, ²​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() t <- rlogis(50, 2.5, 1.4) util_logistic_param_estimate(t)$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> #> 1 Logistic 50 -4.86 7.54 1.99 1.42 EnvSt… 1.99 1.42 1.40 #> 2 Logistic 50 -4.86 7.54 1.99 1.42 EnvSt… 1.99 1.44 1.38 #> 3 Logistic 50 -4.86 7.54 1.99 1.42 EnvSt… 1.99 1.59 1.25 #> # … with abbreviated variable names ¹​location, ²​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_logistic_stats_tbl","title":"Distribution Statistics — util_logistic_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_logistic_stats_tbl","text":"","code":"util_logistic_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_logistic_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_logistic_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_logistic_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_logistic_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_logistic_stats_tbl","text":"","code":"library(dplyr) tidy_logistic() %>% util_logistic_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_logistic\" #> $ function_call \"Logistic c(0, 1)\" #> $ distribution \"Logistic\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode_lower 0 #> $ range \"0 to Inf\" #> $ std_dv 1.813799 #> $ coeff_var 3.289868 #> $ skewness 0 #> $ kurtosis 1.2 #> $ computed_std_skew 0.3656847 #> $ computed_std_kurt 2.531143 #> $ ci_lo -1.871882 #> $ ci_hi 2.833328"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Lognormal Parameters — util_lognormal_param_estimate","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated lognormal data. Three different methods shape parameters supplied: mme, see EnvStats::elnorm() mle, see EnvStats::elnorm()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"","code":"util_lognormal_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"function attempt estimate lognormal meanlog log sd parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_lognormal_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> #> 1 Lognormal 32 10.4 33.9 EnvStats_MVUE 2.96 0.298 9.93 #> 2 Lognormal 32 10.4 33.9 EnvStats_MME 2.96 0.293 10.1 output$combined_data_tbl %>% tidy_combined_autoplot() tb <- tidy_lognormal(.meanlog = 2, .sdlog = 1) %>% pull(y) util_lognormal_param_estimate(tb)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> #> 1 Lognormal 50 1.59 112. EnvStats_MVUE 2.42 0.898 2.70 #> 2 Lognormal 50 1.59 112. EnvStats_MME 2.42 0.889 2.73"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_lognormal_stats_tbl","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"","code":"util_lognormal_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_lognormal_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"","code":"library(dplyr) tidy_lognormal() %>% util_lognormal_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_lognormal\" #> $ function_call \"Lognormal c(0, 1)\" #> $ distribution \"Lognormal\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1.648721 #> $ median 1 #> $ mode 0.3678794 #> $ range \"0 to Inf\" #> $ std_dv 2.161197 #> $ coeff_var 1.310832 #> $ skewness 6.184877 #> $ kurtosis 113.9364 #> $ computed_std_skew 1.464458 #> $ computed_std_kurt 4.975176 #> $ ci_lo 0.1740245 #> $ ci_hi 3.078619"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated negative binomial data. Two different methods shape parameters supplied: MLE/MME MMUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"","code":"util_negative_binomial_param_estimate(.x, .size, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":".x vector data passed function. .size size parameter. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"function attempt estimate negative binomial size prob parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- as.integer(mtcars$mpg) output <- util_negative_binomial_param_estimate(x, .size = 1) output$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean method size prob shape…¹ #> #> 1 Negative Binomial 32 10 33 19.7 EnvStats_M… 32 0.0483 662 #> 2 Negative Binomial 32 10 33 19.7 EnvStats_M… 32 0.0469 682. #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() t <- rnbinom(50, 1, .1) util_negative_binomial_param_estimate(t, .size = 1)$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean method size prob shape…¹ #> #> 1 Negative Binomial 50 0 56 12.6 EnvStats_M… 50 0.0734 681 #> 2 Negative Binomial 50 0 56 12.6 EnvStats_M… 50 0.0721 694. #> # … with abbreviated variable name ¹​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_negative_binomial_stats_tbl","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"","code":"util_negative_binomial_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"","code":"library(dplyr) tidy_negative_binomial() %>% util_negative_binomial_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_negative_binomial\" #> $ function_call \"Negative Binomial c(1, 0.1)\" #> $ distribution \"Negative_binomial\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1111111 #> $ mode_lower 0 #> $ range \"0 to Inf\" #> $ std_dv 0.3513642 #> $ coeff_var 0.1234568 #> $ skewness 3.478505 #> $ kurtosis 14.1 #> $ computed_std_skew 1.164844 #> $ computed_std_kurt 4.061276 #> $ ci_lo 0 #> $ ci_hi 31.55"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated normal data. Three different methods shape parameters supplied: MLE/MME MVUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"","code":"util_normal_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"function attempt estimate normal gaussian mean standard deviation parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_normal_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mu stan_dev shape_ratio #> #> 1 Gaussian 32 10.4 33.9 EnvStats_MME_MLE 20.1 5.93 3.39 #> 2 Gaussian 32 10.4 33.9 EnvStats_MVUE 20.1 6.03 3.33 output$combined_data_tbl %>% tidy_combined_autoplot() t <- rnorm(50, 0, 1) util_normal_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mu stan_dev shape_ratio #> #> 1 Gaussian 50 -2.62 2.63 EnvStats_MME_MLE 0.162 1.12 0.146 #> 2 Gaussian 50 -2.62 2.63 EnvStats_MVUE 0.162 1.13 0.144"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_normal_stats_tbl","title":"Distribution Statistics — util_normal_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_normal_stats_tbl","text":"","code":"util_normal_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_normal_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_normal_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_normal_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_normal_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_normal_stats_tbl","text":"","code":"library(dplyr) tidy_normal() %>% util_normal_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_gaussian\" #> $ function_call \"Gaussian c(0, 1)\" #> $ distribution \"Gaussian\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ median -0.1220474 #> $ mode 0 #> $ std_dv 1 #> $ coeff_var Inf #> $ skewness 0 #> $ kurtosis 3 #> $ computed_std_skew -0.02719793 #> $ computed_std_kurt 2.264517 #> $ ci_lo -1.63738 #> $ ci_hi 1.30215"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Pareto Parameters — util_pareto_param_estimate","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated pareto data. Two different methods shape parameters supplied: LSE MLE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"","code":"util_pareto_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"function attempt estimate pareto shape scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_pareto_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Pareto 32 10.4 33.9 LSE 13.7 2.86 4.79 #> 2 Pareto 32 10.4 33.9 MLE 10.4 1.62 6.40 output$combined_data_tbl %>% tidy_combined_autoplot() t <- tidy_pareto(50, 1, 1) %>% pull(y) util_pareto_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Pareto 50 0.0296 32.8 LSE 0.146 0.497 0.293 #> 2 Pareto 50 0.0296 32.8 MLE 0.0296 0.280 0.106"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_pareto_stats_tbl","title":"Distribution Statistics — util_pareto_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_pareto_stats_tbl","text":"","code":"util_pareto_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_pareto_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_pareto_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_pareto_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_pareto_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_pareto_stats_tbl","text":"","code":"library(dplyr) tidy_pareto() %>% util_pareto_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_pareto\" #> $ function_call \"Pareto c(10, 0.1)\" #> $ distribution \"Pareto\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1111111 #> $ mode_lower 0.1 #> $ range \"0 to Inf\" #> $ std_dv 0.0124226 #> $ coeff_var 0.000154321 #> $ skewness 2.811057 #> $ kurtosis 14.82857 #> $ computed_std_skew 1.242909 #> $ computed_std_kurt 3.929721 #> $ ci_lo 0.0002854128 #> $ ci_hi 0.03200106"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Poisson Parameters — util_poisson_param_estimate","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated poisson data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"","code":"util_poisson_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"function attempt estimate pareto lambda parameter given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- as.integer(mtcars$mpg) output <- util_poisson_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> #> 1 Posson 32 10 33 MLE 19.7 output$combined_data_tbl %>% tidy_combined_autoplot() t <- rpois(50, 5) util_poisson_param_estimate(t)$parameter_tbl #> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> #> 1 Posson 50 1 14 MLE 5.46"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_poisson_stats_tbl","title":"Distribution Statistics — util_poisson_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_poisson_stats_tbl","text":"","code":"util_poisson_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_poisson_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_poisson_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_poisson_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_poisson_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_poisson_stats_tbl","text":"","code":"library(dplyr) tidy_poisson() %>% util_poisson_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_poisson\" #> $ function_call \"Poisson c(1)\" #> $ distribution \"Poisson\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ mode 1 #> $ range \"0 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 1 #> $ kurtosis 4 #> $ computed_std_skew 0.9220841 #> $ computed_std_kurt 3.30817 #> $ ci_lo 0 #> $ ci_hi 3"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_t_stats_tbl","title":"Distribution Statistics — util_t_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_t_stats_tbl","text":"","code":"util_t_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_t_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_t_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_t_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_t_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_t_stats_tbl","text":"","code":"library(dplyr) tidy_t() %>% util_t_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_t\" #> $ function_call \"T Distribution c(1, 0)\" #> $ distribution \"T\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ median 0 #> $ mode 0 #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness 0 #> $ kurtosis \"undefined\" #> $ computed_std_skew -1.587054 #> $ computed_std_kurt 9.068707 #> $ ci_lo -8.367309 #> $ ci_hi 7.548309"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Uniform Parameters — util_uniform_param_estimate","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated uniform data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"","code":"util_uniform_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"function attempt estimate uniform min max parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_uniform(.min = 1, .max = 3)$y output <- util_uniform_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method min_est max_est ratio #> #> 1 Uniform 50 1.00 3.00 NIST_MME 1.09 3.09 0.354 #> 2 Uniform 50 1.00 3.00 NIST_MLE 1 3 0.333 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_uniform_stats_tbl","title":"Distribution Statistics — util_uniform_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_uniform_stats_tbl","text":"","code":"util_uniform_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_uniform_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_uniform_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_uniform_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_uniform_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_uniform_stats_tbl","text":"","code":"library(dplyr) tidy_uniform() %>% util_uniform_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 16 #> $ tidy_function \"tidy_uniform\" #> $ function_call \"Uniform c(0, 1)\" #> $ distribution \"Uniform\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.5 #> $ median 0.5 #> $ std_dv 0.2886751 #> $ coeff_var 0.5773503 #> $ skewness 0 #> $ kurtosis 1.8 #> $ computed_std_skew 0.05112003 #> $ computed_std_kurt 1.603629 #> $ ci_lo 0.01375033 #> $ ci_hi 0.939009"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Weibull Parameters — util_weibull_param_estimate","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated weibull data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"","code":"util_weibull_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"function attempt estimate weibull shape scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_weibull(.shape = 1, .scale = 2)$y output <- util_weibull_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Weibull 50 0.0206 9.67 NIST 0.937 2.14 0.437 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_weibull_stats_tbl","title":"Distribution Statistics — util_weibull_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_weibull_stats_tbl","text":"","code":"util_weibull_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_weibull_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_weibull_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_weibull_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_weibull_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_weibull_stats_tbl","text":"","code":"library(dplyr) tidy_weibull() %>% util_weibull_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 16 #> $ tidy_function \"tidy_weibull\" #> $ function_call \"Weibull c(1, 1)\" #> $ distribution \"Weibull\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.7684299 #> $ median 0.5917829 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 0.8937609 #> $ coeff_var 0.7988085 #> $ computed_std_skew 1.053184 #> $ computed_std_kurt 3.430189 #> $ ci_lo 0.006940537 #> $ ci_hi 2.409566"},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-development-version","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity (development version)","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-development-version","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity (development version)","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvments-development-version","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvments","title":"TidyDensity (development version)","text":"Fix #210 - Fix param_grid order internal affected attributes thus display order parameters. Fix #211 - Add High Low CI tidy_distribution_summary_tbl() Fix #213 - Use purrr::compact() list distributions passed order prevent issue occurring #212 Fix #212 - Make tidy_distribution_comparison() robust terms handling bad erroneous data. Fix #216 - Add attribute “tibble_type” tidy_multi_single_dist() helps work functions like tidy_random_walk()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-120","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.0","title":"TidyDensity 1.2.0","text":"CRAN release: 2022-06-08","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.0","text":"Fix #181 - Add functions color_blind() td_scale_fill_colorblind() td_scale_color_colorblind() Fix #187 - Add functions ci_lo() ci_hi() Fix #189 - Add function tidy_bootstrap() Fix #190 - Add function bootstrap_unnest_tbl() Fix #202 - Add function tidy_distribution_comparison()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-2-0","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.2.0","text":"Fix #176 - Update _autoplot functions include cumulative mean MCMC chart taking advantage .num_sims parameter tidy_ distribution functions. Fix #184 - Update tidy_empirical() add parameter .distribution_type Fix #183 - tidy_empirical() now plotted _autoplot functions. Fix #188 - Add .num_sims parameter tidy_empirical() Fix #196 - Add ci_lo() ci_hi() stats tbl functions. Fix #201 - Correct attribute distribution_family_type discrete tidy_geometric()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-110","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.1.0","title":"TidyDensity 1.1.0","text":"CRAN release: 2022-05-06","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-1-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.1.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-1-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.1.0","text":"Fix #119 - Add function tidy_four_autoplot() - auto plot density, qq, quantile probability plots single graph. Fix #125 - Add function util_weibull_param_estimate() Fix #126 - Add function util_uniform_param_estimate() Fix #127 - Add function util_cauchy_param_estimate() Fix #130 - Add function tidy_t() - Also add plotting functions. Fix #151 - Add function tidy_mixture_density() Fix #150 - Add function util_geometric_stats_tbl() Fix #149 - Add function util_hypergeometric_stats_tbl() Fix #148 - Add function util_logistic_stats_tbl() Fix #147 - Add function util_lognormal_stats_tbl() Fix #146 - Add function util_negative_binomial_stats_tbl() Fix #145 - Add function util_normal_stats_tbl() Fix #144 - Add function util_pareto_stats_tbl() Fix #143 - Add function util_poisson_stats_tbl() Fix #142 - Add function util_uniform_stats_tbl() Fix #141 - Add function util_cauchy_stats_tbl() Fix #140 - Add function util_t_stats_tbl() Fix #139 - Add function util_f_stats_tbl() Fix #138 - Add function util_chisquare_stats_tbl() Fix #137 - Add function util_weibull_stats_tbl() Fix #136 - Add function util_gamma_stats_tbl() Fix #135 - Add function util_exponential_stats_tbl() Fix #134 - Add function util_binomial_stats_tbl() Fix #133 - Add function util_beta_stats_tbl()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-1-0","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.1.0","text":"Fix #110 - Bug fix, correct p calculation tidy_poisson() now produce correct probability chart auto plot functions. Fix #112 - Bug fix, correct p calculation tidy_hypergeometric() produce correct probability chart auto plot functions. Fix #115 - Fix spelling Quantile chart. Fix #117 - Fix probability plot x axis label. Fix #118 - Fix fill color combined auto plot Fix #122 - tidy_distribution_summary_tbl() function take output tidy_multi_single_dist() Fix #166 - Change plotting functions ggplot2::xlim(0, max_dy) ggplot2::ylim(0, max_dy) Fix #169 - Fix computation q column Fix #170 - Fix graphing quantile chart due #169","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-101","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.0.1","title":"TidyDensity 1.0.1","text":"CRAN release: 2022-03-27","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-0-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.0.1","text":"Fix #91 - Bug fix, change tidy_gamma() parameter .rate .scale Fixtidy_autoplot_functions incorporate change. Fixutil_gamma_param_estimate()sayscaleinstead ofrate` returned estimated parameters.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-0-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.0.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-0-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.0.1","text":"Fix #90 - Make sure .geom_smooth set TRUE ggplot2::xlim(0, max_dy) set. Fix #100 - tidy_multi_single_dist() failed distribution single parameter like tidy_poisson() Fix #96 - Enhance tidy_ distribution functions add attribute either discrete continuous helps autoplot process. Fix #97 - Enhance tidy_autoplot() use histogram lines density plot depending distribution discrete continuous. Fix #99 - Enhance tidy_multi_dist_autoplot() use histogram lines density plot depending distribution discrete continuous.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-100","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.0.0","title":"TidyDensity 1.0.0","text":"CRAN release: 2022-03-08","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-0-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.0.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-0-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.0.0","text":"Fix #27 - Add function tidy_binomial() Fix #32 - Add function tidy_geometric() Fix #33 - Add function tidy_negative_binomial() Fix #34 - Add function tidy_zero_truncated_poisson() Fix #35 - Add function tidy_zero_truncated_geometric() Fix #36 - Add function tidy_zero_truncated_binomial() Fix #37 - Add function tidy_zero_truncated_negative_binomial() Fix #41 - Add function tidy_pareto1() Fix #42 - Add function tidy_pareto() Fix #43 - Add function tidy_inverse_pareto() Fix #58 - Add function tidy_random_walk() Fix #60 - Add function tidy_random_walk_autoplot() Fix #47 - Add function tidy_generalized_pareto() Fix #44 - Add function tidy_paralogistic() Fix #38 - Add function tidy_inverse_exponential() Fix #45 - Add function tidy_inverse_gamma() Fix #46 - Add function tidy_inverse_weibull() Fix #48 - Add function tidy_burr() Fix #49 - Add function tidy_inverse_burr() Fix #50 - Add function tidy_inverse_normal() Fix #51 - Add function tidy_generalized_beta() Fix #26 - Add function tidy_multi_single_dist() Fix #62 - Add function tidy_multi_dist_autoplot() Fix #66 - Add function tidy_combine_distributions() Fix #69 - Add functions tidy_kurtosis_vec(), tidy_skewness_vec(), tidy_range_statistic() Fix #75 - Add function util_beta_param_estimate() Fix #76 - Add function util_binomial_param_estimate() Fix #77 - Add function util_exponential_param_estimate() Fix #78 - Add function util_gamma_param_estimate() Fix #79 - Add function util_geometric_param_estimate() Fix #80 - Add function util_hypergeometric_param_estimate() Fix #81 - Add function util_lognormal_param_estimate() Fix #89 - Add function tidy_scale_zero_one_vec() Fix #87 - Add function tidy_combined_autoplot() Fix #82 - Add function util_logistic_param_estimate() Fix #83 - Add function util_negative_binomial_param_estimate() Fix #84 - Add function util_normal_param_estimate() Fix #85 - Add function util_pareto_param_estimate() Fix #86 - Add function util_poisson_param_estimate()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"fixes-and-minor-improvements-1-0-0","dir":"Changelog","previous_headings":"","what":"Fixes and Minor Improvements","title":"TidyDensity 1.0.0","text":"Fix #30 - Move crayon, rstudioapi, cli Suggests Imports due pillar longer importing. Fix #52 - Add parameter .geom_rug tidy_autoplot() function Fix #54 - Add parameter .geom_point tidy_autoplot() function Fix #53 - Add parameter .geom_smooth tidy_autoplot() function Fix #55 - Add parameter .geom_jitter tidy_autoplot() function Fix #57 - Fix tidy_autoplot() distribution tidy_empirical() legend argument fail. Fix #56 - Add attributes .n .num_sims (1L now) tidy_empirical() Fix #61 - Update _pkgdown.yml file update site. Fix #67 - Add param_grid, param_grid_txt, dist_with_params attributes tidy_ distribution functions. Fix #70 - Add ... grouping parameter tidy_distribution_summary_tbl() Fix #88 - Make column dist_type factor tidy_combine_distributions()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-001","dir":"Changelog","previous_headings":"","what":"TidyDensity 0.0.1","title":"TidyDensity 0.0.1","text":"CRAN release: 2022-01-21","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-0-0-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 0.0.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-0-0-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 0.0.1","text":"Fix #1 - Add function tidy_normal() Fix #4 - Add function tidy_gamma() Fix #5 - Add function tidy_beta() Fix #6 - Add function tidy_poisson() Fix #2 - Add function tidy_autoplot() Fix #11 - Add function tidy_distribution_summary_tbl() Fix #10 - Add function tidy_empirical() Fix #13 - Add function tidy_uniform() Fix #14 - Add function tidy_exponential() Fix #15 - Add function tidy_logistic() Fix #16 - Add function tidy_lognormal() Fix #17 - Add function tidy_weibull() Fix #18 - Add function tidy_chisquare() Fix #19 - Add function tidy_cauchy() Fix #20 - Add function tidy_hypergeometric() Fix #21 - Add function tidy_f()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-0-0-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 0.0.1","text":"None","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 0.0.0.9000","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 0.0.0.9000","text":"Added NEWS.md file track changes package.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"fixes-and-minor-improvements-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"Fixes and Minor Improvements","title":"TidyDensity 0.0.0.9000","text":"None","code":""}]