Posterior predictive checks for bml models

Graphical posterior predictive checks via bayesplot (must be installed). Compares the observed outcome with replicated outcomes from posterior_predict.bml.

Usage

pp_check(object, ...)

# S3 method for class 'bml'
pp_check(object, type = NULL, ndraws = 30, ...)

Arguments

object

A fitted bml model (gaussian or bernoulli, fitted with monitor = TRUE).

...

Passed to the bayesplot function.

type

A bayesplot PPC type (without the "ppc_" prefix), e.g. "dens_overlay" (default for gaussian), "bars" (default for bernoulli), "hist", "stat".

ndraws

Number of replicated datasets to plot. Default: 30.

Value

A ggplot object.