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Plot posterior draws

Source: R/posterior.R
plot.RprobitB_fit.Rd

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")