do some target stan tests

tests/testthat/test-stan-primary_censored_dist_analytical_cdf.R

@@ -0,0 +1,108 @@
+test_that(
+  "Stan primary_censored_dist_analytical_lcdf matches R implementation for
+   Gamma",
+  {
+    shapes <- c(0.5, 1, 2, 5)
+    rates <- c(0.1, 0.5, 1, 2)
+    pwindows <- c(1, 2, 5, 10)
+
+    for (shape in shapes) {
+      for (rate in rates) {
+        for (pwindow in pwindows) {
+          obj <- new_primary_censored_dist(
+            pgamma,
+            dunif, list(),
+            "pgamma", "dunif",
+            shape = shape, rate = rate
+          )
+
+          q_values <- seq(0, 30, by = 1)
+          r_result <- primary_censored_cdf(
+            obj,
+            q = q_values, pwindow = pwindow, use_numeric = FALSE
+          )
+
+          stan_result <- vapply(q_values, function(q) {
+            primary_censored_dist_analytical_cdf(
+              q, 2, c(shape, rate), pwindow, Inf, 1, numeric(0)
+            )
+          }, numeric(1))
+          expect_equal(r_result, stan_result, tolerance = 1e-6)
+        }
+      }
+    }
+  }
+)
+
+test_that(
+  "Stan primary_censored_dist_analytical_lcdf matches R implementation for
+   Lognormal",
+  {
+    meanlogs <- c(-1, 0, 1, 2)
+    sdlogs <- c(0.5, 1, 1.5)
+    pwindows <- c(1, 2, 5, 8)
+
+    for (meanlog in meanlogs) {
+      for (sdlog in sdlogs) {
+        for (pwindow in pwindows) {
+          obj <- new_primary_censored_dist(
+            plnorm,
+            dunif, list(),
+            "plnorm", "dunif",
+            meanlog = meanlog, sdlog = sdlog
+          )
+
+          q_values <- seq(0, 30, by = 1)
+          r_result <- primary_censored_cdf(
+            obj,
+            q = q_values, pwindow = pwindow, use_numeric = FALSE
+          )
+
+          stan_result <- vapply(q_values, function(q) {
+            primary_censored_dist_analytical_cdf(
+              q, 1, c(meanlog, sdlog), pwindow, Inf, 1, numeric(0)
+            )
+          }, numeric(1))
+          expect_equal(r_result, stan_result, tolerance = 1e-6)
+        }
+      }
+    }
+  }
+)
+
+test_that(
+  "Stan primary_censored_dist_analytical_lcdf matches R implementation for
+   Weibull",
+  {
+    shapes <- c(0.5, 1, 2, 3)
+    scales <- c(0.5, 1, 2, 5)
+    pwindows <- c(1, 2, 5, 10)
+
+    for (shape in shapes) {
+      for (scale in scales) {
+        for (pwindow in pwindows) {
+          obj <- new_primary_censored_dist(
+            pweibull,
+            dunif, list(),
+            "pweibull", "dunif",
+            shape = shape, scale = scale
+          )
+
+          q_values <- seq(0, 30, by = 1)
+          r_result <- primary_censored_cdf(
+            obj,
+            q = q_values, pwindow = pwindow, use_numeric = FALSE
+          )
+
+          stan_result <- vapply(q_values, function(q) {
+            primary_censored_dist_analytical_cdf(
+              q, 3, c(shape, scale), pwindow, Inf, 1, numeric(0)
+            )
+          }, numeric(1))
+
+          expect_equal(r_result, stan_result, tolerance = 1e-6)
+        }
+      }
+    }
+  }
+)