R: Posterior Predictive Checks for 'brmsfit' Objects

pp_check.brmsfit {brms}

R Documentation

Posterior Predictive Checks for `brmsfit` Objects

Description

Perform posterior predictive checks with the help of the bayesplot package.

Usage

## S3 method for class 'brmsfit'
pp_check(
  object,
  type,
  ndraws = NULL,
  nsamples = NULL,
  group = NULL,
  x = NULL,
  newdata = NULL,
  resp = NULL,
  draw_ids = NULL,
  subset = NULL,
  ...
)

Arguments

`object`	An object of class `brmsfit`.
`type`	Type of the ppc plot as given by a character string. See `PPC` for an overview of currently supported types. You may also use an invalid type (e.g. `type = "xyz"`) to get a list of supported types in the resulting error message.
`ndraws`	Positive integer indicating how many posterior draws should be used. If `NULL` all draws are used. If not specified, the number of posterior draws is chosen automatically. Ignored if `draw_ids` is not `NULL`.
`nsamples`	Deprecated alias of `ndraws`.
`group`	Optional name of a factor variable in the model by which to stratify the ppc plot. This argument is required for ppc `*_grouped` types and ignored otherwise.
`x`	Optional name of a variable in the model. Only used for ppc types having an `x` argument and ignored otherwise.
`newdata`	An optional data.frame for which to evaluate predictions. If `NULL` (default), the original data of the model is used. `NA` values within factors are interpreted as if all dummy variables of this factor are zero. This allows, for instance, to make predictions of the grand mean when using sum coding.
`resp`	Optional names of response variables. If specified, predictions are performed only for the specified response variables.
`draw_ids`	An integer vector specifying the posterior draws to be used. If `NULL` (the default), all draws are used.
`subset`	Deprecated alias of `draw_ids`.
`...`	Further arguments passed to `predict.brmsfit` as well as to the PPC function specified in `type`.

Details

For a detailed explanation of each of the ppc functions, see the PPC documentation of the bayesplot package.

Value

A ggplot object that can be further customized using the ggplot2 package.

Examples

## Not run: 
fit <-  brm(count ~ zAge + zBase * Trt
            + (1|patient) + (1|obs),
            data = epilepsy, family = poisson())

pp_check(fit)  # shows dens_overlay plot by default
pp_check(fit, type = "error_hist", ndraws = 11)
pp_check(fit, type = "scatter_avg", ndraws = 100)
pp_check(fit, type = "stat_2d")
pp_check(fit, type = "rootogram")
pp_check(fit, type = "loo_pit")

## get an overview of all valid types
pp_check(fit, type = "xyz")

## End(Not run)

[Package brms version 2.16.3 Index]