plot.RprobitB_fit: Plot posterior draws

In RprobitB: Bayesian Probit Choice Modeling

Plot posterior draws

Description

Creates a standard posterior diagnostic or uncertainty plot with bayesplot.

Usage

## S3 method for class 'RprobitB_fit'
plot(
  x,
  y = NULL,
  type = c("trace", "rank", "acf", "density", "interval", "pairs"),
  variables = NULL,
  ...
)

Arguments

x	[RprobitB_fit] Fitted choice model.
y	[NULL] Currently not used.
type	[character(1)] The plot to create: "trace" draws the sampled values of each chain over the iterations. "rank" compares the chains through the ranks of their draws. "acf" draws the autocorrelation within each chain. "density" overlays the marginal posterior density of each chain. "interval" draws posterior point estimates with credible intervals. "pairs" draws bivariate scatter plots of the variables.
variables	[character() | NULL] Posterior variables to include. NULL includes all varying model parameters and excludes individual coefficients and latent allocations.
...	Further arguments passed to the selected bayesplot function.

Value

A ggplot object or, for a pairs plot, a bayesplot_grid object.

Examples

set.seed(1)
model <- fit(
  choice ~ x + z | 0, dgp_parameters = list(beta = c(x = 1, z = -0.5)),
  chains = 2
)

### convergence and mixing of the chains
plot(model, type = "trace")
plot(model, type = "rank")
plot(model, type = "acf")

### marginal and joint posterior distributions
plot(model, type = "density")
plot(model, type = "interval")
plot(model, type = "pairs")

RprobitB documentation built on Sept. 20, 2026, 9:07 a.m.