model_summaries()
datasummary_log.Rd
Runs model_summaries()
on all models in the input and returns a subset of the each resulting summary as a tibble.
summary_log(.base_dir, .recurse = TRUE, ...) add_summary(.log_df, ...)
.base_dir | Base directory to look in for models. |
---|---|
.recurse | If |
... | Arguments passed through to |
.log_df | a |
An object of class bbi_summary_log_df
, which includes the fields described below. If all model summaries
fail, the returned tibble will only contain the absolute_model_path
, run
, and error_msg
columns.
summary_log()
creates a new tibble with one row per model
found in .base_dir
(and subdirectories, if .recurse = TRUE
).
add_summary()
adds these fields to the tibble passed to .log_df
.
The following fields from bbi_nonmem_summary
(the output of model_summary()
) are extracted and included by default.
If you would like more fields from the summary object, you can extract them manually from the bbi_summary
list column.
error_msg
-- Error message from model_summary()
. If NULL
the call succeeded. If not NULL
, the rest of the fields will be NULL
.
needed_fail_flags
-- Logical for whether the call initially failed, but passed with the inclusion of .fail_flags
. See model_summaries()
docs for more details.
bbi_summary
-- The full bbi_nonmem_summary
object for each row. This can be queried further by extracting it as a list, or by using dplyr::mutate()
etc.
ofv
-- Objective function value with no constant from the final estimation method. The constant, and the value with the constant can be found in $ofv
.
param_count
-- Count of (non-fixed) parameters estimated in final estimation method.
estimation_method
-- Character vector of estimation method(s) used. Extracted from $run_details
.
problem_text
-- Character vector of text from $PROB
. Extracted from $run_details
.
number_of_subjects
-- Count of unique subjects in the input data set, extracted from $run_details
.
number_of_obs
-- Total count of observations in the input data set, extracted from $run_details
.
condition_number
-- The condition number for the final estimation method, if present.
any_heuristics
-- Logical indicating whether any of the columns extracted from $run_heuristics
are TRUE
. Duplicative information, but helpful for filtering.
$run_heuristics
columns -- One logical column for each element extracted from $run_heuristics
. These are named and described in the model_summary()
docs.