Bmix: Bayesian Sampling for Stick-Breaking Mixtures
Version 0.6

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.

AuthorMatt Taddy <taddy@chicagobooth.edu>
Date of publication2016-02-07 09:18:19
MaintainerMatt Taddy <taddy@chicagobooth.edu>
LicenseGPL (>= 2)
Version0.6
URL http://faculty.chicagobooth.edu/matt.taddy
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("Bmix")

Popular man pages

mix: Bayesian inference for (dynamic) stick-breaking mixtures
particle: Reading particle files
See all...

All man pages Function index File listing

Man pages

mix: Bayesian inference for (dynamic) stick-breaking mixtures
particle: Reading particle files

Functions

Files

src
src/matrix.cc
src/Makevars
src/randomkit.h
src/rvtools.c
src/rhelp.c
src/rvtools.h
src/latools.h
src/randomkit.c
src/rhelp.h
src/mix.cc
src/particle.cc
src/particle.h
src/latools.c
src/matrix.h
NAMESPACE
demo
demo/pines.R
demo/bar2D.R
demo/alpha.R
demo/DPreg.R
demo/bar1D.R
demo/00Index
R
R/mix.R
MD5
DESCRIPTION
man
man/mix.Rd
man/particle.Rd
Bmix documentation built on May 19, 2017, 7:03 a.m.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs in the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.