This function takes a bbi_nmboot_model
(created by a previous
new_bootstrap_run()
call) and creates n
new model objects and re-sampled
datasets in a subdirectory. The control stream found at
get_model_path(.boot_run)
is used as the "template" for these new model
objects, and the new datasets are sampled from the dataset defined in its
$DATA
record (i.e. get_data_path(.boot_run)
).
setup_bootstrap_run(
.boot_run,
n = 200,
strat_cols = NULL,
seed = 1234,
data = NULL,
.bbi_args = list(no_grd_file = TRUE, no_shk_file = TRUE),
.overwrite = FALSE
)
A bbi_nmboot_model
object.
Number of data sets and model runs to generate.
Columns to maintain proportion for stratification
A numeric seed to set prior to resampling the data; use NULL
to
avoid setting a seed.
A dataset to resample from. Defaults to NULL
, which will use
the filtered output from nm_data(.boot_run, filter = TRUE)
. If provided,
must include the same column names as what's returned from nm_data(.mod)
.
Named list passed to model_summary(orig_mod, .bbi_args)
,
where orig_mod
is the model .boot_run
is based on. See
print_bbi_args()
for valid options. Defaults to list(no_grd_file = TRUE, no_shk_file = TRUE)
because model_summary()
is only called internally to
extract the number of records, so those files are irrelevant. Only used if
the based on model (the model being bootstrapped) has been executed.
Logical (T/F) indicating whether or not to overwrite existing setup for a bootstrap run.
Once you have run this function, you can execute your bootstrap with
submit_model()
. You can use get_model_status()
to check on your submitted
bootstrap run. Once all models have finished, use summarize_bootstrap_run()
to view the results. See examples below.
if (FALSE) {
# Setup
.boot_run <- new_bootstrap_run(.mod)
.boot_run <- setup_bootstrap_run(
.boot_run,
n = 1000,
seed = 1234,
strat_cols = c("STUDY", "ETN")
)
# Submit
submit_model(.boot_run)
# Check status of runs during submission
get_model_status(.boot_run)
# Summarize results, once all runs have finished
if (check_nonmem_finished(.boot_run)) {
.boot_sum <- summarize_bootstrap_run(.boot_run)
}
}