We have provided some sample code to help you understand MCMC techniques such as Gibbs sampling, Metropolis, and Gibbs-Metropolis.

Note that all of the faculty examples use the data in faculty.dat

## Rejection Sampling

Recall that rejection sampling is not effective with continuous-valued evidence nodes. However, we include it here because it's simple.

## Gibbs Sampling

In the following example, Gibbs sampling is used with sampling from the complete conditionals.

## Metropolis

In the following example, the Metropolis algorithm is used to sample from a Cauchy distribution.

## Gibbs-Metropolis Combo

This code implements a combo MCMC algorithm using Gibbs sampling, with Metropolis sampling at each node:

## Evilplot

Evilplot files are listed below. A simple way to get everything needed for evilplot is to run the following command:

  git clone git://aml.cs.byu.edu/evilplot.git