Support performance_simres class

NAMESPACE

@@ -64,6 +64,7 @@ S3method(plot,see_parameters_sem)
 S3method(plot,see_parameters_simulate)
 S3method(plot,see_performance_pp_check)
 S3method(plot,see_performance_roc)
+S3method(plot,see_performance_simres)
 S3method(plot,see_point_estimate)
 S3method(plot,see_rope)
 S3method(plot,see_si)

R/data_plot.R

@@ -148,6 +148,11 @@ add_plot_attributes <- function(x) {
   obj_name <- attr(x, "object_name", exact = TRUE)
   dat <- NULL
 
+  # for simulated residuals, we save all necessary information in the object
+  if (inherits(x, "performance_simres")) {
+    return(x$fittedModel)
+  }
+
   if (!is.null(obj_name)) {
     # first try, parent frame
     dat <- tryCatch(get(obj_name, envir = parent.frame()), error = function(e) NULL)

R/plot.check_normality.R

@@ -24,7 +24,7 @@
 #'
 #' @return A ggplot2-object.
 #'
 #' @seealso See also the vignette about [`check_model()`](https://easystats.github.io/performance/articles/check_model.html).
 #'
 #' @examplesIf require("performance")
 #' m <<- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
@@ -70,7 +70,10 @@
   } else {
     if (type == "qq") { # nolint
       model_info <- attributes(x)$model_info
-      if (inherits(model, c("lme", "lmerMod", "merMod", "afex_aov", "BFBayesFactor"))) {
+      if (inherits(x, "performance_simres")) {
+        dat <- stats::na.omit(data.frame(y = x$scaledResiduals))
+        model_info$is_simulated_residuals <- TRUE
+      } else if (inherits(model, c("lme", "lmerMod", "merMod", "glmmTMB", "afex_aov", "BFBayesFactor"))) {
         res_ <- suppressMessages(sort(stats::residuals(model), na.last = NA))
         dat <- stats::na.omit(data.frame(y = res_))
       } else if (inherits(model, "glmmTMB")) {
@@ -97,7 +100,11 @@
         model_class = class(model)[1]
       )
     } else if (type == "density") {
-      r <- suppressMessages(stats::residuals(model))
+      if (inherits(x, "performance_simres")) {
+        r <- attributes(x)$data
+      } else {
+        r <- suppressMessages(stats::residuals(model))
+      }
       dat <- as.data.frame(bayestestR::estimate_density(r))
       dat$curve <- stats::dnorm(
         seq(min(dat$x), max(dat$x), length.out = nrow(dat)),
@@ -106,7 +113,11 @@
       )
       .plot_diag_norm(dat, size_line = size_line)
     } else if (type == "pp") {
-      x <- suppressMessages(sort(stats::residuals(model), na.last = NA))
+      if (inherits(x, "performance_simres")) {
+        x <- attributes(x)$data
+      } else {
+        x <- suppressMessages(sort(stats::residuals(model), na.last = NA))
+      }
       dat <- data.frame(res = x)
       .plot_diag_pp(
         dat,
@@ -122,6 +133,10 @@
 }
 
 
+#' @export
+plot.see_performance_simres <- plot.see_check_normality
+
+
 # normality plot: density -------------------------
 
 .plot_diag_norm <- function(x,
@@ -174,7 +189,7 @@
                           model_class = NULL) {
   qhalfnorm <- function(p) stats::qnorm((p + 1) / 2)
   # qq-halfnorm for GLM
-  if (isTRUE(model_info$is_binomial) || isTRUE(model_info$is_count)) {
+  if (!isTRUE(model_info$is_simulated_residuals) && (isTRUE(model_info$is_binomial) || isTRUE(model_info$is_count))) {
     gg_init <- ggplot2::ggplot(x, ggplot2::aes(x = .data$x, y = .data$y))
     qq_stuff <- list(
       ggplot2::geom_point(
@@ -240,7 +255,7 @@
         )
       },
       ggplot2::geom_qq(
         mapping = if (detrend) ggplot2::aes(y = ggplot2::after_stat(.data$sample) - ggplot2::after_stat(.data$theoretical)),
         shape = 16,
         na.rm = TRUE,
         stroke = 0,