Package: Bmix
Type: Package
Title: Bayesian Sampling for Stick-Breaking Mixtures
Version: 0.6
Author: Matt Taddy <taddy@chicagobooth.edu>
Maintainer: Matt Taddy <taddy@chicagobooth.edu>
Description: 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.
License: GPL (>= 2)
Depends: mvtnorm
URL: http://faculty.chicagobooth.edu/matt.taddy
NeedsCompilation: yes
Packaged: 2016-02-06 20:55:28 UTC; mtaddy
Repository: CRAN
Date/Publication: 2016-02-07 09:18:19
Built: R 4.0.2; x86_64-apple-darwin17.0; 2020-07-15 09:40:42 UTC; unix
Archs: Bmix.so.dSYM
