add tests

tests/testthat/test-check_outliers.R

@@ -342,3 +342,40 @@ test_that("check_outliers with invald data", {
     regex = "No numeric variables found"
   )
 })
+
+
+test_that("check_outliers with DHARMa", {
+  skip_if_not_installed("DHARMa")
+  mt1 <- mtcars[, c(1, 3, 4)]
+  # create some fake outliers and attach outliers to main df
+  mt2 <- rbind(mt1, data.frame(
+    mpg = c(37, 40), disp = c(300, 400),
+    hp = c(110, 120)
+  ))
+  # fit model with outliers
+  model <- lm(disp ~ mpg + hp, data = mt2)
+  set.seed(123)
+  res <- simulate_residuals(model)
+  out <- check_outliers(res)
+  expect_equal(
+    out,
+    structure(
+      list(
+        Coefficient = 0.0294117647058824, Expected = 0.00796812749003984,
+        CI_low = 0.000744364234690261, CI_high = 0.153267669560318,
+        p_value = 0.238146844116552
+      ),
+      class = c("check_outliers_simres", "list")
+    ),
+    ignore_attr = TRUE,
+    tolerance = 1e-4
+  )
+  expect_identical(
+    capture.output(print(out)),
+    c(
+      "# Outliers detection", "", "  Proportion of observed outliers: 2.94%",
+      "  Proportion of expected outliers: 0.80%, 95% CI [0.07, 15.33]",
+      ""
+    )
+  )
+})