draft plot for check_residuals

NAMESPACE

@@ -38,6 +38,7 @@ S3method(plot,see_check_model)
 S3method(plot,see_check_normality)
 S3method(plot,see_check_outliers)
 S3method(plot,see_check_overdisp)
+S3method(plot,see_check_residuals)
 S3method(plot,see_compare_parameters)
 S3method(plot,see_compare_performance)
 S3method(plot,see_effectsize_table)
@@ -64,6 +65,7 @@ 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/plot.performance_simres.R

@@ -0,0 +1,108 @@
+#' Plot method for check model for (non-)normality of residuals
+#'
+#' The `plot()` method for the `performance::check_residuals()` resp.
+#' `performance::simulate_residuals()` function.
+#'
+#' @inheritParams plot.see_check_normality
+#'
+#' @return A ggplot2-object.
+#'
+#' @seealso See also the vignette about [`check_model()`](https://easystats.github.io/performance/articles/check_model.html).
+#'
+#' @examplesIf require("performance") && require("glmmTMB") && require("qqplotr")
+#' data(Salamanders, package = "glmmTMB")
+#' model <- glmmTMB::glmmTMB(
+#'   count ~ mined + spp + (1 | site),
+#'   family = poisson(),
+#'   data = Salamanders
+#' )
+#' simulated_residuals <- performance::simulate_residuals(model)
+#' plot(simulated_residuals)
+#'
+#' # or
+#' simulated_residuals <- performance::simulate_residuals(model)
+#' result <- performance::check_residuals(simulated_residuals)
+#' plot(result)
+#'
+#' @export
+plot.see_performance_simres <- function(x,
+                                        size_line = 0.8,
+                                        size_point = 1,
+                                        alpha = 0.2,
+                                        dot_alpha = 0.8,
+                                        colors = c("#3aaf85", "#1b6ca8"),
+                                        detrend = FALSE,
+                                        ...) {
+  dp <- list(min = 0, max = 1, lower.tail = TRUE, log.p = FALSE)
+
+  # base plot information
+  gg_init <- ggplot2::ggplot(
+    data.frame(scaled_residuals = stats::residuals(x)),
+    ggplot2::aes(sample = scaled_residuals)
+  )
+
+  # when we have package qqplotr, we can add confidence bands
+  if (requireNamespace("qqplotr", quietly = TRUE)) {
+    qq_stuff <- list(
+      qqplotr::stat_qq_band(
+        distribution = "unif",
+        dparams = list(min = 0, max = 1),
+        alpha = alpha,
+        detrend = detrend
+      ),
+      qqplotr::stat_qq_line(
+        distribution = "unif",
+        dparams = dp,
+        size = size_line,
+        colour = colors[1],
+        detrend = detrend
+      ),
+      qqplotr::stat_qq_point(
+        distribution = "unif",
+        dparams = dp,
+        size = size_point,
+        alpha = dot_alpha,
+        colour = colors[2],
+        detrend = detrend
+      )
+    )
+    if (detrend) {
+      y_lab <- "Sample Quantile Deviations"
+    } else {
+      y_lab <- "Sample Quantiles"
+    }
+  } else {
+    insight::format_alert("For confidence bands, please install `qqplotr`.")
+    qq_stuff <- list(
+      ggplot2::geom_point(
+        shape = 16,
+        stroke = 0,
+        size = size_point,
+        colour = colors[2]
+      ),
+      ggplot2::geom_qq_line(
+        linewidth = size_line,
+        colour = colors[1],
+        na.rm = TRUE
+      )
+    )
+    y_lab <- "Sample Quantiles"
+  }
+
+  gg_init +
+    qq_stuff +
+    ggplot2::labs(
+      title = "Uniformity of Residuals",
+      subtitle = "Dots should fall along the line",
+      x = "Standard Uniform Distribution Quantiles",
+      y = y_lab
+    ) +
+    theme_lucid(
+      base_size = 10,
+      plot.title.space = 3,
+      axis.title.space = 5
+    )
+}
+
+#' @export
+plot.see_check_residuals <- plot.see_performance_simres