A collection of functions for visualizing Markov chain Monte Carlo output in R with the base graphics library and python with matplotlib. While the functions are relatively general they are designed to facilitate the implementation of Bayesian inference, including visual prior checks, visual posterior retrodictive checks, and the visualization of marginal posterior inferences.

Most of the visualization functions assume that Markov chain Monte Carlo output is organized into named lists or dictionaries for R and python, each consisting of two-dimensional arrays indexed by Markov chain and then iteration. This format is also used in https://github.com/betanalpha/mcmc_diagnostics.

Each folder contains an extensive demonstration of the visualization functions applied to Bayesian inference.