sample_model takes an lgpmodel
object and fits it using sampling.
optimize_model takes an lgpmodel
object and fits it using optimizing.
sample_model(
model,
verbose = TRUE,
quiet = FALSE,
skip_postproc = is_f_sampled(model),
...
)
optimize_model(model, ...)An object of class lgpmodel.
Can messages be printed?
Should all output messages be suppressed? You need to set
also refresh=0 if you want to suppress also the progress update
messages from sampling.
Should all postprocessing be skipped? If this is
TRUE, the returned lgpfit object will likely be
much smaller (if sample_f=FALSE).
Optional arguments passed to
sampling or optimizing.
sample_model returns an object of class lgpfit
containing the parameter draws, the original model object,
and possible postprocessing results. See documentation of
lgpfit for more information.
optimize_model directly returns the list returned by
optimizing. See its documentation for more information.
Other main functions:
create_model(),
draw_pred(),
get_draws(),
lgp(),
pred(),
prior_pred()