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.
|Maintainer:||Matt Taddy <taddy at chicagobooth.edu>|
|License:||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]|
|In views:||Bayesian, Cluster|
|CRAN checks:||Bmix results|
|Windows binaries:||r-devel: Bmix_0.6.zip, r-release: Bmix_0.6.zip, r-oldrel: Bmix_0.6.zip|
|OS X El Capitan binaries:||r-release: Bmix_0.6.tgz|
|OS X Mavericks binaries:||r-oldrel: Bmix_0.6.tgz|
|Old sources:||Bmix archive|
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