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-rw-r--r--tests/testthat/test_error_models.R49
1 files changed, 48 insertions, 1 deletions
diff --git a/tests/testthat/test_error_models.R b/tests/testthat/test_error_models.R
index d7a5cea8..fa1f7131 100644
--- a/tests/testthat/test_error_models.R
+++ b/tests/testthat/test_error_models.R
@@ -153,7 +153,7 @@ test_that("Reweighting method 'tc' produces reasonable variance estimates", {
# For a single fit, we get a relative error of less than 10% in the error
# model components
f_met_2_tc_e4 <- mkinfit(m_synth_DFOP_lin, d_met_2_15[[1]], quiet = TRUE,
- error_model = "tc")
+ error_model = "tc", error_model_algorithm = "direct")
parm_errors_met_2_tc_e4 <- (f_met_2_tc_e4$errparms - c(0.5, 0.07)) / c(0.5, 0.07)
expect_true(all(abs(parm_errors_met_2_tc_e4) < 0.1))
@@ -177,3 +177,50 @@ test_that("Reweighting method 'tc' produces reasonable variance estimates", {
# from 15 datasets
expect_true(all(abs(tcf_met_2_15_tc_error_model_errors) < 0.10))
})
+
+test_that("The different error model fitting methods work for parent fits", {
+ skip_on_cran()
+
+ f_9_OLS <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+ quiet = TRUE)
+ expect_equivalent(round(AIC(f_9_OLS), 2), 137.43)
+
+ f_9_direct <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+ error_model = "tc", error_model_algorithm = "direct", quiet = TRUE)
+ expect_equivalent(round(AIC(f_9_direct), 2), 134.94)
+
+ f_9_twostep <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+ error_model = "tc", error_model_algorithm = "twostep", quiet = TRUE)
+ expect_equivalent(round(AIC(f_9_twostep), 2), 134.94)
+
+ f_9_threestep <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+ error_model = "tc", error_model_algorithm = "threestep", quiet = TRUE)
+ expect_equivalent(round(AIC(f_9_threestep), 2), 139.43)
+
+ f_9_fourstep <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+ error_model = "tc", error_model_algorithm = "fourstep", quiet = TRUE)
+ expect_equivalent(round(AIC(f_9_fourstep), 2), 139.43)
+
+ f_9_IRLS <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+ error_model = "tc", error_model_algorithm = "IRLS", quiet = TRUE)
+ expect_equivalent(round(AIC(f_9_IRLS), 2), 139.43)
+
+ f_9_d_3 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+ error_model = "tc", error_model_algorithm = "d_3", quiet = TRUE)
+ expect_equivalent(round(AIC(f_9_d_3), 2), 134.94)
+})
+
+test_that("The default error model algorithm finds the best known AIC values for parent fits", {
+ f_tc_exp_d_3 <- mmkin(c("SFO", "DFOP", "HS"),
+ lapply(experimental_data_for_UBA_2019, function(x) x$data),
+ error_model = "tc",
+ error_model_algorithm = "d_3",
+ quiet = TRUE)
+
+ AIC_exp_d_3 <- lapply(f_tc_exp_d_3, AIC)
+ AIC_exp_d_3 <- lapply(AIC_exp_d_3, round, 1)
+ dim(AIC_exp_d_3) <- dim(f_tc_exp_d_3)
+ dimnames(AIC_exp_d_3) <- dimnames(f_tc_exp_d_3)
+
+ expect_known_output(AIC_exp_d_3, "AIC_exp_d_3.out")
+})

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