use default type dictionary, so we can override when needed

R/get_marginaleffects_type.R

@@ -17,8 +17,9 @@
     return(list(predict = predict, backtransform = FALSE, link_inverse = NULL))
   }
 
-  # extract all valid types for model class
+  # extract all valid types and the default type for model class
   valid_types <- .valid_marginaleffects_types(model)
+  default_type <- .default_marginaleffects_types(model)
 
   # find link-types - we need link-type when user wants bias-correction
   link_types <- c("link", "linear.predictor", "lp")
@@ -72,7 +73,7 @@
   if (is.null(dots$type)) {
     link_inverse <- .link_inverse(model, verbose = verbose, ...)
     if (is.null(predict)) {
-      out <- valid_types[1]
+      out <- default_type
     } else {
       out <- predict
     }
@@ -103,7 +104,7 @@
 }
 
 
-# return default "type" argument - this differs, depending on model class
+# return all "type" arguments
 .valid_marginaleffects_types <- function(model) {
   model_class <- class(model)[1]
   # for unrecognized model classes, return "response"
@@ -115,6 +116,20 @@
 }
 
 
+# return default type argument for model class, as defined in marginaleffecs
+# we can overwrite the default, e.g. using "inverse_link" as an option when
+# not provided by marginaleffects, in the ".default_type" data frame
+.default_marginaleffects_types <- function(model) {
+  model_class <- class(model)[1]
+  # for unrecognized model classes, return "response"
+  if (!model_class %in% .default_type$class) {
+    return("response")
+  }
+  # extract all valid types for model class
+  .default_type$type[.default_type$class == model_class]
+}
+
+
 # all valid "type" arguments for each model class.
 # Run "marginaleffects:::type_dictionary_build()" to update this list
 .typedic <- data.frame(