Bmix (0.6)

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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.

Maintainer: Matt Taddy
Author(s): Matt Taddy <>

License: GPL (>= 2)

Uses: mvtnorm

Released over 3 years ago.

5 previous versions



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