bet.m	Helper function for chibs.m.
chibs.m	An implementation of Chib's method. Uses bet.m.
clust.m	Helper function for mkclust.m.
down_and_in_Call.m	Script for down-and-in call example. Uses function down_in_call.m.
down_in_call.m	Performance function for the down-and-in call example.
findneigh.m	Finds the neighbors of a given site. Used in Potts.m.
HDR (folder)	Holmes-Diaconis-Ross Method.
Hit_and_run.m	Hit-and-run sampler for the truncated multivariate normal distribution. Uses normt2.m.
independence_sampler.m	Sampling on the surface of an ellipsoid using an independence sampler.
logit_model.m	Metropolis-Hastings sampling for the logit model. Uses binornd.m (statistics toolbox).
mkclust.m	Clusters the sites given the auxiliary variables. Used in Potts.m.
multiple_try.m	Multiple-try Metropolis-Hastings sampling from the bimodal two-humps density.
normt.m	Draws from a certain truncated normal distribution via the inverse-transform method.
normt2.m	Draws from another truncated normal distribution via the inverse-transform method.
Potts.m	Sampling from the Potts model via the Swendsen-Wang algorithm. Uses clust.m, findneigh.m, and mkclust.m.
probit_model.m	Sampling from the posterior of a Bayesian probit model using auxilliary variables and the grouped Gibbs sampler. Uses binornd.m (statistics toolbox) and normt.m.
Reversible_jump.m	Implements the reversible jump sampler for model choice in regression.
slice_sampler.m	Samples (approximately) from a gamma distribution via the slice sampler. Uses kde.m from Chapter 8, and gamcdf.m and gampdf.m (statistics toolbox) for plotting.
snb_polyhedron.m	Samples (approximately) uniformly on the surface of a polytope via the shake-and-bake sampler.
zip.m	Gibbs sampling for the ZIP model. Uses betarnd.m, gamrnd.m, and poissrnd.m (statistics toolbox).

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