better conditional_effect plots; better error propagation of mgcv models

NAMESPACE

@@ -111,6 +111,9 @@ importFrom(brms,pstudent_t)
 importFrom(brms,qstudent_t)
 importFrom(brms,rstudent_t)
 importFrom(brms,student)
+importFrom(ggplot2,scale_colour_discrete)
+importFrom(ggplot2,scale_fill_discrete)
+importFrom(ggplot2,theme_classic)
 importFrom(grDevices,devAskNewPage)
 importFrom(grDevices,hcl.colors)
 importFrom(grDevices,rgb)

R/conditional_effects.R

@@ -3,6 +3,7 @@
 #' Display conditional effects of one or more numeric and/or categorical
 #' predictors in `mvgam` models, including two-way interaction effects.
 #' @importFrom brms conditional_effects
+#' @importFrom ggplot2 scale_colour_discrete scale_fill_discrete theme_classic
 #' @importFrom marginaleffects plot_predictions
 #' @importFrom graphics plot
 #' @importFrom grDevices devAskNewPage
@@ -114,7 +115,8 @@ conditional_effects.mvgam = function(x,
                                      rug = rug,
                                      ...) +
           scale_fill_discrete(label = roundlabs) +
-          scale_colour_discrete(label = roundlabs)
+          scale_colour_discrete(label = roundlabs) +
+          theme_classic()
 
       }
 
@@ -128,7 +130,8 @@ conditional_effects.mvgam = function(x,
                                      rug = rug,
                                      ...) +
           scale_fill_discrete(label = roundlabs) +
-          scale_colour_discrete(label = roundlabs)
+          scale_colour_discrete(label = roundlabs) +
+          theme_classic()
       }
 
       if(length(cond_labs[[i]]) == 3){
@@ -142,7 +145,8 @@ conditional_effects.mvgam = function(x,
                                      rug = rug,
                                      ...) +
           scale_fill_discrete(label = roundlabs) +
-          scale_colour_discrete(label = roundlabs)
+          scale_colour_discrete(label = roundlabs) +
+          theme_classic()
       }
 
 
@@ -161,7 +165,6 @@ conditional_effects.mvgam = function(x,
 plot.mvgam_conditional_effects = function(x,
                                           plot = TRUE,
                                           ask = FALSE,
-                                          theme = NULL,
                                           ...){
   out <- x
   for(i in seq_along(out)){

R/get_mvgam_priors.R

@@ -479,10 +479,8 @@ get_mvgam_priors = function(formula,
         stop(paste('Missing values found in data predictors:\n',
                    attr(ss_gam, 'condition')),
              call. = FALSE)
-      }
-
-      if(grepl('fewer unique', ss_gam[1])){
-        stop('A term has fewer unique covariate combinations than specified maximum degrees of freedom',
+      } else {
+        stop(paste(ss_gam[1]),
              call. = FALSE)
       }
     }

R/mvgam.R

@@ -755,10 +755,8 @@ mvgam = function(formula,
       stop(paste('Missing values found in data predictors:\n',
                  attr(ss_gam, 'condition')),
            call. = FALSE)
-    }
-
-    if(grepl('fewer unique', ss_gam[1])){
-      stop('A term has fewer unique covariate combinations than specified maximum degrees of freedom',
+    } else {
+      stop(paste(ss_gam[1]),
            call. = FALSE)
     }
   }