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Posterior Predictive Checks For Mcpfit Objects

Source: R/pp_check.R
pp_check.Rd

Plot posterior (default) or prior (prior = TRUE) predictive checks. This is convenience wrapper around the bayesplot::ppc_*() methods.

Usage

pp_check(
  object,
  type = "dens_overlay",
  facet_by = NULL,
  newdata = NULL,
  prior = FALSE,
  varying = TRUE,
  arma = TRUE,
  ndraws = 100,
  nsamples = lifecycle::deprecated(),
  ...
)

Arguments

object

An mcpfit object.

type

One of bayesplot::available_ppc("grouped", invert = TRUE) %>% stringr::str_remove("ppc_")

facet_by

Name of a column in data modeled as varying effect(s).

newdata

A tibble or a data.frame containing predictors in the model. Weighted Gaussian predictions and log-likelihoods also require the weights column. If NULL (default), the original data is used.

prior

TRUE/FALSE. Plot using prior samples? Useful for mcp(..., sample = "both")

varying

One of:

  • TRUE All varying effects (fit$pars$varying).

  • FALSE No varying effects (c()).

  • "cp" or "predictor": All varying effects belonging to that part of the model.

  • Character vector: Only include specified varying parameters - see fit$pars$varying.

arma

Whether to include AR and MA effects.

  • TRUE Compute the GARMA residual recurrence. Requires the response variable in newdata.

  • FALSE Disregard AR and MA effects. For family = gaussian(), predict() uses only sigma for residuals.

ndraws

Number of posterior draws. Note that you may want to use all draws for summary geoms, e.g., pp_check(fit, type = "ribbon", ndraws = NULL). LOO checks always evaluate all posterior draws to preserve their PSIS weights; where supported, ndraws is passed to bayesplot to control the number of plotted samples.

nsamples

Deprecated. Use ndraws instead.

...

Further arguments passed to bayesplot::ppc_type(y, yrep, ...)

Value

A ggplot2 object for single plots. Enriched by patchwork for faceted plots.

Details

Missing responses are omitted from the observed-data check. LOO predictive checks use posterior draws and the original fitted data, so they do not support prior = TRUE or newdata.

See also

plot.mcpfit pp_eval

plot_pars plot_dpar pp_check

Author

Jonas Kristoffer Lindeløv jonas@lindeloev.dk

Examples

# \donttest{
pp_check(demo_fit)

pp_check(demo_fit, type = "ecdf_overlay")

#pp_check(some_varying_fit, type = "loo_intervals", facet_by = "id")
# }