sample_model: Fitting a model

In jtimonen/lgpr: Longitudinal Gaussian Process Regression

Fitting a model

Description

• sample_model takes an lgpmodel object and fits it using sampling.

• optimize_model takes an lgpmodel object and fits it using optimizing.

Usage

sample_model(
  model,
  verbose = TRUE,
  quiet = FALSE,
  skip_postproc = is_f_sampled(model),
  ...
)

optimize_model(model, ...)

Arguments

model	An object of class lgpmodel.
verbose	Can messages be printed?
quiet	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.
skip_postproc	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.

Value

• 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.

See Also

Other main functions: create_model(), draw_pred(), get_draws(), lgp(), pred(), prior_pred()

jtimonen/lgpr documentation built on Sept. 15, 2024, 1:08 a.m.