Bmix: Bayesian Sampling for Stick-Breaking Mixtures

This is a bare-bones implementation of sampling algorithms for a variety of Bayesian stick-breaking (marginally DP) mixture models, including particle learning and Gibbs sampling for static DP mixtures, particle learning for dynamic BAR stick-breaking, and DP mixture regression. The software is designed to be easy to customize to suit different situations and for experimentation with stick-breaking models. Since particles are repeatedly copied, it is not an especially efficient implementation.

Version: 0.6
Depends: mvtnorm
Published: 2016-02-07
Author: Matt Taddy
Maintainer: Matt Taddy <taddy at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: Bayesian, Cluster
CRAN checks: Bmix results


Reference manual: Bmix.pdf
Package source: Bmix_0.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: Bmix_0.6.tgz, r-oldrel: Bmix_0.6.tgz
Old sources: Bmix archive


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