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authorJohannes Ranke <jranke@uni-bremen.de>2021-03-09 17:35:47 +0100
committerJohannes Ranke <jranke@uni-bremen.de>2021-03-09 17:35:47 +0100
commitc73b2f30ec836c949885784ab576e814eb8070a9 (patch)
tree7cfff70c5dae646fb464f4071e4ec444bbf40de1 /tests/testthat/setup_script.R
parent9a414d01985f9177745ce0ad234ef7fc1b9822bb (diff)
Some improvements for borderline cases
- fit_with_errors for saem() - test_log_parms for mean_degparms() and saem()
Diffstat (limited to 'tests/testthat/setup_script.R')
-rw-r--r--tests/testthat/setup_script.R19
1 files changed, 17 insertions, 2 deletions
diff --git a/tests/testthat/setup_script.R b/tests/testthat/setup_script.R
index 9229c198..96e865d4 100644
--- a/tests/testthat/setup_script.R
+++ b/tests/testthat/setup_script.R
@@ -106,6 +106,7 @@ const <- function(value) 2
set.seed(123456)
SFO <- mkinmod(parent = mkinsub("SFO"))
k_parent = rlnorm(n, log(0.03), log_sd)
+set.seed(123456)
ds_sfo <- lapply(1:n, function(i) {
ds_mean <- mkinpredict(SFO, c(k_parent = k_parent[i]),
c(parent = 100), sampling_times)
@@ -118,6 +119,7 @@ fomc_pop <- list(parent_0 = 100, alpha = 2, beta = 8)
fomc_parms <- as.matrix(data.frame(
alpha = rlnorm(n, log(fomc_pop$alpha), 0.4),
beta = rlnorm(n, log(fomc_pop$beta), 0.2)))
+set.seed(123456)
ds_fomc <- lapply(1:3, function(i) {
ds_mean <- mkinpredict(FOMC, fomc_parms[i, ],
c(parent = 100), sampling_times)
@@ -131,6 +133,7 @@ dfop_parms <- as.matrix(data.frame(
k1 = rlnorm(n, log(dfop_pop$k1), log_sd),
k2 = rlnorm(n, log(dfop_pop$k2), log_sd),
g = plogis(rnorm(n, qlogis(dfop_pop$g), log_sd))))
+set.seed(123456)
ds_dfop <- lapply(1:n, function(i) {
ds_mean <- mkinpredict(DFOP, dfop_parms[i, ],
c(parent = dfop_pop$parent_0), sampling_times)
@@ -144,6 +147,7 @@ hs_parms <- as.matrix(data.frame(
k1 = rlnorm(n, log(hs_pop$k1), log_sd),
k2 = rlnorm(n, log(hs_pop$k2), log_sd),
tb = rlnorm(n, log(hs_pop$tb), 0.1)))
+set.seed(123456)
ds_hs <- lapply(1:10, function(i) {
ds_mean <- mkinpredict(HS, hs_parms[i, ],
c(parent = hs_pop$parent_0), sampling_times)
@@ -171,6 +175,7 @@ ds_biphasic_mean <- lapply(1:n_biphasic,
c(parent = 100, m1 = 0), sampling_times)
}
)
+set.seed(123456)
ds_biphasic <- lapply(ds_biphasic_mean, function(ds) {
add_err(ds,
sdfunc = function(value) sqrt(err_1$const^2 + value^2 * err_1$prop^2),
@@ -193,8 +198,18 @@ nlme_biphasic <- nlme(mmkin_biphasic)
if (saemix_available) {
sfo_saem_1 <- saem(mmkin_sfo_1, quiet = TRUE, transformations = "saemix")
- dfop_saemix_1 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "mkin")
- dfop_saemix_2 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "saemix")
+ # With default control parameters, we do not get good results with mkin
+ # transformations here
+ dfop_saemix_1 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "mkin",
+ control = list(
+ displayProgress = FALSE, print = FALSE, save = FALSE, save.graphs = FALSE,
+ rw.init = 1, nbiter.saemix = c(600, 100))
+ )
+ dfop_saemix_2 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "saemix",
+ control = list(
+ displayProgress = FALSE, print = FALSE, save = FALSE, save.graphs = FALSE,
+ rw.init = 0.5, nbiter.saemix = c(600, 100))
+ )
saem_biphasic_m <- saem(mmkin_biphasic, transformations = "mkin", quiet = TRUE)
saem_biphasic_s <- saem(mmkin_biphasic, transformations = "saemix", quiet = TRUE)

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