Posterior Predictive Checks for brmcoda Objects — pp

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

Usage

# S3 method for class 'brmcoda'
pp_check(
  object,
  type = "dens_overlay",
  ndraws = NULL,
  prefix = c("ppc", "ppd"),
  newdata = NULL,
  draw_ids = NULL,
  nsamples = NULL,
  subset = NULL,
  scale = c("linear", "response"),
  parts = NULL,
  ...
)

Arguments

object: An object of class brmcoda.
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.
prefix: The prefix of the bayesplot function to be applied. Either `"ppc"` (posterior predictive check; the default) or `"ppd"` (posterior predictive distribution), the latter being the same as the former except that the observed data is not shown for `"ppd"`.
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 (excluding grouping variables) 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. NA values within grouping variables are treated as a new level.
draw_ids: An integer vector specifying the posterior draws to be used. If NULL (the default), all draws are used.
nsamples: Deprecated alias of ndraws.
subset: Deprecated alias of draw_ids.
scale: Specifically for models with compositional responses, either "response" or "linear". If "linear", results are returned on the log-ratio scale. If "response", results are returned on the compositional scale of the response variable.
parts: Optional names or indices of compositional response parts to include when scale = "response". If NULL, all parts are used.
...: Further arguments passed to predict.brmsfit as well as to the PPC function specified in type.

Examples

# \donttest{
if(requireNamespace("cmdstanr")){
  ## fit a model
  x <- complr(data = mcompd, sbp = sbp,
                 parts = c("TST", "WAKE", "MVPA", "LPA", "SB"),
                 idvar = "ID", total = 1440)

  m1 <- brmcoda(complr = x,
                formula = Stress ~ bz1_1 + bz2_1 + bz3_1 + bz4_1 +
                                   wz1_1 + wz2_1 + wz3_1 + wz4_1 + (1 | ID),
                chain = 1, iter = 500,
                backend = "cmdstanr")

  ## posterior predictive checks
  bayesplot::pp_check(m1, ndraws = 5)

  ## fit a model with compositional outcome
  m2 <- brmcoda(complr = x,
                formula = mvbind(z1_1, z2_1, z3_1, z4_1) ~ 
                          bz1_1 + bz2_1 + bz3_1 + bz4_1 + Female + (1 | ID),
                chain = 1, iter = 500,
                backend = "cmdstanr")

  ## posterior predictive checks for compositional outcome -- linear scale
  bayesplot::pp_check(m2, resp = "z11", ndraws = 10)
  ## posterior predictive checks for compositional outcome -- original response scale
  bayesplot::pp_check(m2, parts = "WAKE", scale = "response", ndraws = 10)
}# }
#> Error: CmdStan path has not been set yet. See ?set_cmdstan_path.

Posterior Predictive Checks for `brmcoda` Objects

Usage

Arguments

See also

Examples