Add tests for autocorrelation with simulated residuals and update overdispersion test

Co-authored-by: strengejacke <26301769+strengejacke@users.noreply.github.com>

Author: Copilot

tests/testthat/test-check_autocorrelation_simres.R

@@ -0,0 +1,47 @@
+test_that("check_autocorrelation works with simulated residuals", {
+  skip_if_not_installed("DHARMa")
+  skip_if_not_installed("glmmTMB")
+  skip_if_not(getRversion() >= "4.0.0")
+  
+  data(Salamanders, package = "glmmTMB")
+  
+  # Test with a simple Poisson GLM
+  m <- glm(count ~ spp + mined, family = poisson, data = Salamanders)
+  
+  # Simulate residuals
+  set.seed(123)
+  simres <- simulate_residuals(m)
+  
+  # Check autocorrelation
+  set.seed(123)
+  out <- check_autocorrelation(simres)
+  
+  # Should return a p-value
+  expect_type(out, "double")
+  expect_s3_class(out, "check_autocorrelation")
+  
+  # P-value should be between 0 and 1
+  expect_true(out >= 0 && out <= 1)
+})
+
+
+test_that("check_autocorrelation.DHARMa works", {
+  skip_if_not_installed("DHARMa")
+  
+  # Test that the DHARMa method works
+  data(mtcars)
+  m <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
+  
+  set.seed(123)
+  simres <- DHARMa::simulateResiduals(m, plot = FALSE)
+  
+  set.seed(123)
+  out <- check_autocorrelation(simres)
+  
+  # Should return a p-value
+  expect_type(out, "double")
+  expect_s3_class(out, "check_autocorrelation")
+  
+  # P-value should be between 0 and 1
+  expect_true(out >= 0 && out <= 1)
+})

tests/testthat/test-check_overdispersion.R

@@ -50,6 +50,7 @@ test_that("check_overdispersion, glmmTMB-poisson", {
 
 test_that("check_overdispersion, glmmTMB-poisson mixed", {
   skip_if_not_installed("glmmTMB")
+  skip_if_not_installed("DHARMa")
   skip_if_not(getRversion() >= "4.0.0")
   data(Salamanders, package = "glmmTMB")
 
@@ -58,19 +59,20 @@ test_that("check_overdispersion, glmmTMB-poisson mixed", {
     family = poisson,
     data = Salamanders
   )
+  # Poisson mixed models now use simulated residuals (see #595, #643)
+  set.seed(123)
+  out <- check_overdispersion(m2)
   expect_equal(
-    check_overdispersion(m2),
+    out,
     structure(
       list(
-        chisq_statistic = 1475.87512547128,
-        dispersion_ratio = 2.32421279601777,
-        residual_df = 635L,
-        p_value = 8.41489530177729e-69
+        dispersion_ratio = 3.30,
+        p_value = 0
       ),
-      class = c("check_overdisp", "see_check_overdisp"),
-      object_name = "m2"
+      class = c("check_overdisp", "see_check_overdisp")
     ),
-    tolerance = 1e-3
+    tolerance = 0.1,
+    ignore_attr = TRUE
   )
 })