Reject degenerate recovery simulations

Author: soodoku

NEWS.md

@@ -31,6 +31,9 @@
 * DK model summaries and validation examples correctly identify learning as
   `gk + dk`.
 
+* `validate_recovery()` now rejects degenerate generating models at the
+  parameter boundary, where recovery diagnostics are not meaningful.
+
 # version 0.7.0 2026-08-02
 
 This release incorporates 0.6.0, which was tagged but never submitted to

R/model-criticism.R

@@ -666,7 +666,7 @@ cross_sectional_learning_score <- function(
 #' Performs Monte Carlo simulations to assess parameter recovery of the
 #' LCA model. Useful for validating estimator performance.
 #'
-#' @param true_params Named numeric vector of true parameters.
+#' @param true_params Named numeric vector of strictly interior true parameters.
 #'   For no-DK model: c(gg=, gk=, kk=, gamma=)
 #'   For DK model: c(gg=, gk=, gd=, kk=, dg=, dk=, dd=, gamma=)
 #' @param n Integer. Sample size per simulation. Default 500.
@@ -735,8 +735,20 @@ validate_recovery <- function(true_params, n = 500, n_items = 2,
         abs(sum(class_weights) - 1) > sqrt(.Machine$double.eps)) {
     stop("Latent-class weights in true_params must be probabilities that sum to 1.", call. = FALSE)
   }
-  if (true_params[["gamma"]] < 0 || true_params[["gamma"]] > 1) {
-    stop("true_params$gamma must be a probability between 0 and 1.", call. = FALSE)
+  if (any(class_weights == 0 | class_weights == 1)) {
+    stop(
+      paste(
+        "Latent-class weights in true_params must be strictly between 0 and 1",
+        "for recovery validation."
+      ),
+      call. = FALSE
+    )
+  }
+  if (true_params[["gamma"]] <= 0 || true_params[["gamma"]] >= 1) {
+    stop(
+      "true_params$gamma must be strictly between 0 and 1 for recovery validation.",
+      call. = FALSE
+    )
   }
 
   estimates <- with_preserved_seed(seed, {

man/validate_recovery.Rd

@@ -164,6 +164,19 @@ test_that("validate_recovery requires a named feasible generating model", {
     validate_recovery(invalid_gamma, n = 100, n_sims = 2),
     "gamma"
   )
+  boundary_weight <- valid
+  boundary_weight["gg"] <- 0
+  boundary_weight["kk"] <- 0.70
+  expect_error(
+    validate_recovery(boundary_weight, n = 100, n_sims = 2),
+    "strictly between"
+  )
+  boundary_gamma <- valid
+  boundary_gamma["gamma"] <- 0
+  expect_error(
+    validate_recovery(boundary_gamma, n = 100, n_sims = 2),
+    "strictly between"
+  )
 })
 
 test_that("validate_recovery preserves caller RNG state", {
@@ -176,12 +189,12 @@ test_that("validate_recovery preserves caller RNG state", {
   expect_identical(before, after)
 })
 
-test_that("validate_recovery surfaces a failed replicate", {
+test_that("validate_recovery rejects degenerate generating models", {
   degenerate <- c(gg = 0, gk = 0, kk = 1, gamma = 0)
 
   expect_error(
     validate_recovery(degenerate, n = 10, n_items = 1, n_sims = 1, seed = 1),
-    "Simulation 1 failed: Optimization did not converge"
+    "strictly between"
   )
 })