Fixes #465

NEWS.md

@@ -6,13 +6,14 @@ None
 ## New Features
 1. #468 - Add function `util_negative_binomial_aic()` to calculate the AIC for the negative binomial distribution.
 2. #470 - Add function `util_ztn_binomial_param_estimate()` and `util_rztnbinom_aic()` to estimate the parameters and calculate the AIC for the zero-truncated negative binomial distribution. Also added `util_ztn_binomial_stats_tbl()`
-3. #467 - Add function `util_zero_truncated_poisson_param_estimate()` to estimate
+3. #471 - Add function `util_zero_truncated_poisson_param_estimate()` to estimate
 the parameters of the zero-truncated Poisson distribution. Add function `util_zero_truncated_poisson_aic()` to calculate the AIC for the zero-truncated Poisson distribution. Add function `util_zero_truncated_poisson_stats_tbl()` to create a summary table of the zero-truncated Poisson distribution.
 4. #472 - Add function `util_f_param_estimate()` and `util_f_aic()` to estimate the parameters and calculate the AIC for the F distribution.
 
 ## Minor Improvements and Fixes
 1. Fix #468 - Update `util_negative_binomial_param_estimate()` to add the use of
 `optim()` for parameter estimation.
+2. Fix #465 - Add names to columns when `.return_tibble = TRUE` for `quantile_normalize()`
 
 # TidyDensity 1.4.0
 

R/utils-quantile-normalize.R

@@ -41,8 +41,8 @@
 #'   sapply(function(x) quantile(x, probs = seq(0, 1, 1 / 4)))
 #'
 #' quantile_normalize(
-#' data.frame(sample1 = rnorm(30),
-#'            sample2 = rnorm(30)),
+#' data.frame(rnorm(30),
+#'            rnorm(30)),
 #'            .return_tibble = TRUE)
 #'
 #' @seealso
@@ -137,15 +137,15 @@ quantile_normalize <- function(.data, .return_tibble = FALSE) {
     )
   }
 
-  return(
-    list(
-      normalized_data = normalized_data,
-      row_means = row_means,
-      #sorted_data = sorted_data,
-      #column_rank_indices = rank_indices,
-      duplicated_ranks = duplicated_ranks,
-      duplicated_rank_row_indices = duplicated_rank_vector,
-      duplicated_rank_data = duplicated_rank_data
-    )
+  output <- list(
+    normalized_data = normalized_data,
+    row_means = row_means,
+    #sorted_data = sorted_data,
+    #column_rank_indices = rank_indices,
+    duplicated_ranks = duplicated_ranks,
+    duplicated_rank_row_indices = duplicated_rank_vector,
+    duplicated_rank_data = duplicated_rank_data
   )
+
+  return(output)
 }