allow worm plots as a diagnostic in appraise as per #62

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: gratia
-Version: 0.8.1.8
+Version: 0.8.1.9
 Date: 2023-02-21
 Title: Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'
 Authors@R: c(person(given = "Gavin L.", family = "Simpson",

NEWS.md

@@ -1,4 +1,4 @@
-# gratia 0.8.1.8
+# gratia 0.8.1.9
 
 ## User visible changes
 
@@ -16,7 +16,7 @@
 
 ## New features
 
-* `data_sim()` can now simulate response data from Tweedie and ordered
+* `data_sim()` can now simulate response data from gamma, Tweedie and ordered
   categorical distributions.
 
 * `fitted_samples()` and `smooth_samples()` can now use the Metropolis Hastings
@@ -47,6 +47,9 @@
 
 * `link()` and `inv_link()` work for models fitted using the `cnorm()` family.
 
+* A worm plot can now be drawn in place of the QQ plot with `appraise()` via
+  new argument `use_worm = TRUE`. #62
+
 ## Bug fixes
 
 * `link()`, `inv_link()`, and related family functions for the `ocat()` weren't

R/diagnose.R

@@ -618,10 +618,11 @@
 }
 
 #' @title Model diagnostic plots
-#' 
+#'
 #' @param model a fitted model. Currently only class `"gam"`.
 #' @param method character; method used to generate theoretical quantiles. Note
 #'   that `method = "direct"` is deprecated in favour of `method = "uniform"`.
+#' @param use_worm logical; should a worm plot be drawn in place of the QQ plot?
 #' @param n_uniform numeric; number of times to randomize uniform quantiles
 #'   in the direct computation method (`method = "direct"`) for QQ plots.
 #' @param n_simulate numeric; number of data sets to simulate from the estimated
@@ -681,6 +682,7 @@
 #' @export
 `appraise.gam` <- function(model,
                        method = c("uniform", "simulate", "normal", "direct"),
+                       use_worm = FALSE,
                        n_uniform = 10, n_simulate = 50,
                        type = c("deviance", "pearson", "response"),
                        n_bins = c("sturges", "scott", "fd"),
@@ -707,10 +709,17 @@
              paste(dQuote(c("sturges", "scott", "fd")), collapse = ", "))
     }
 
-    plt1 <- qq_plot(model, method = method, type = type, n_uniform = n_uniform,
-                    n_simulate = n_simulate, level = level, ci_alpha = ci_alpha,
-                    point_col = point_col, point_alpha = point_alpha,
-                    line_col = line_col)
+    plt1 <- if (isTRUE(use_worm)) {
+        worm_plot(model, method = method, type = type, n_uniform = n_uniform,
+            n_simulate = n_simulate, level = level, ci_alpha = ci_alpha,
+            point_col = point_col, point_alpha = point_alpha,
+            line_col = line_col)
+    } else {
+        qq_plot(model, method = method, type = type, n_uniform = n_uniform,
+            n_simulate = n_simulate, level = level, ci_alpha = ci_alpha,
+            point_col = point_col, point_alpha = point_alpha,
+            line_col = line_col)
+    }
     plt2 <- residuals_linpred_plot(model, type = type, point_col = point_col,
                                    point_alpha = point_alpha,
                                    line_col = line_col)

tests/testthat/test-diagnostic-plots.R

@@ -110,4 +110,11 @@ test_that("appraise works for a LM", {
     set.seed(1)
     expect_silent(plt <- appraise(m_lm))
     expect_doppelganger("appraise lm ", plt)
+})
+
+test_that("appraise can use the worm plot", {
+    set.seed(1)
+    expect_silent(plt <- appraise(m_gam, use_worm = TRUE,
+        method = "simulate"))
+    expect_doppelganger("appraise worm plot", plt)
 })