Summarizes the parameter estimates from tibble like what's returned from
param_estimates_batch()
, showing you the quantiles passed to probs
,
likely interpreted as confidence intervals for your parameter estimates.
Optionally takes an "original model" to compare these quantiles against.
Originally conceived for comparing a model to multiple runs of the "same"
model, for example in a bootstrap or simulation.
A tibble with columns for each parameter and rows for each
model (like what's returned from param_estimates_batch()
)
bbi_model
object to compare .param_df
against. If
NULL
, the default, only returns quantiles from .param_df
. If passed,
will display an additional original_estimate
column.
An expression that can be passed to dplyr::select()
to
select which columns in .param_df
will be pivoted and summarized.
Defaults to dplyr::starts_with(c("THETA", "SIGMA", "OMEGA"))
(designed
for NONMEM runs), but consider using dplyr::matches()
to select columns
using regex. Also see
?tidyselect::language
for more details and options.
Numeric vector with values between 0 and 1 to be passed through to
stats::quantile()
. Represents the quantiles to calculate for parameter
estimates in .param_df
.
Logical scalar, passed through to stats::quantile()
.
A tibble with the first column containing the parameter names (that
were column names in .param_df
), the second column optionally containing
original parameter estimates (if .orig_mod
is passed), and subsequent
columns containing the quantiles specified in probs
. You can think of
this as essentially .param_df
, summarized by quantiles across all rows,
and then pivoted.