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).