posterior_plot: Plot Posterior Distributions from SGLD Samples

In ngme2: Linear Latent Non-Gaussian Models with Flexible Distributions

Plot Posterior Distributions from SGLD Samples

Description

Visualize marginal posterior distributions of parameters extracted from [ngme_sgld_samples()] or summarized by [ngme_sgld_ci()].

Usage

posterior_plot(
  x,
  parameters = NULL,
  type = c("density", "histogram"),
  by_chain = FALSE,
  show_estimate = TRUE,
  show_interval = TRUE,
  lower = NULL,
  upper = NULL,
  bins = 30,
  ncol = NULL,
  ...
)

## S3 method for class 'ngme_sgld_ci'
plot(x, ...)

Arguments

x	a data.frame (or list of data.frames) returned by [ngme_sgld_samples()], or an object of class 'ngme_sgld_ci'.
parameters	optional character vector of parameter names to plot. Defaults to all parameter columns.
type	character; '"density"' (default) or '"histogram"'.
by_chain	logical; if 'TRUE', color distributions by chain when a '.chain' column is available.
show_estimate	logical; add a vertical line at the posterior mean.
show_interval	logical; add vertical lines for the equal-tail interval.
lower	lower quantile probability used for intervals. If 'x' is an 'ngme_sgld_ci' object, the stored value is used by default.
upper	upper quantile probability used for intervals. If 'x' is an 'ngme_sgld_ci' object, the stored value is used by default.
bins	number of bins for histograms.
ncol	number of facet columns. If 'NULL', use 2 columns for multiple parameters and 1 for a single parameter.
...	unused.

Value

A faceted ggplot object.

ngme2 documentation built on May 20, 2026, 9:10 a.m.