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authorJohannes Ranke <jranke@uni-bremen.de>2023-11-23 05:20:17 +0100
committerJohannes Ranke <jranke@uni-bremen.de>2023-11-23 05:33:55 +0100
commita1b5d63e031d22b190e9e9fc30753b699ad6b4ea (patch)
treed2c2cd104e08681568b1293ef3266396b702a619 /tests/testthat/test_saemix_parent.R
parent8b7edd4eaf0d196e674a085f744d1a69260a6c91 (diff)
fix: 'R/illparms.R': An ill-defined random effect is now also found if there is only one random effect in the model. Also add a test for this.
Diffstat (limited to 'tests/testthat/test_saemix_parent.R')
-rw-r--r--tests/testthat/test_saemix_parent.R27
1 files changed, 27 insertions, 0 deletions
diff --git a/tests/testthat/test_saemix_parent.R b/tests/testthat/test_saemix_parent.R
index 7fbecd0c..c80b4fa1 100644
--- a/tests/testthat/test_saemix_parent.R
+++ b/tests/testthat/test_saemix_parent.R
@@ -148,3 +148,30 @@ test_that("We can also use mkin solution methods for saem", {
rel_diff <- abs(distimes_dfop_analytical - distimes_dfop) / distimes_dfop
expect_true(all(rel_diff < 0.01))
})
+
+test_that("illparms finds a single random effect that is ill-defined", {
+ set.seed(123456)
+ n <- 4
+ SFO <- mkinmod(parent = mkinsub("SFO"))
+ sfo_pop <- list(parent_0 = 100, k_parent = 0.03)
+ sfo_parms <- as.matrix(data.frame(
+ k_parent = rlnorm(n, log(sfo_pop$k_parent), 0.001)))
+ sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+ err_1 = list(const = 1, prop = 0.05)
+ tc <- function(value) sigma_twocomp(value, err_1$const, err_1$prop)
+ set.seed(123456)
+ ds_sfo <- lapply(1:n, function(i) {
+ ds_mean <- mkinpredict(SFO, sfo_parms[i, ],
+ c(parent = sfo_pop$parent_0), sampling_times)
+ add_err(ds_mean, tc, n = 1)[[1]]
+ })
+ m_mmkin <- mmkin("SFO", ds_sfo, error_model = "tc", quiet = TRUE)
+ m_saem_1 <- saem(m_mmkin)
+ expect_equal(
+ as.character(illparms(m_saem_1)),
+ c("sd(parent_0)", "sd(log_k_parent)"))
+ m_saem_2 <- saem(m_mmkin, no_random_effect = "parent_0")
+ expect_equal(
+ as.character(illparms(m_saem_2)),
+ "sd(log_k_parent)")
+}

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