Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models

Model-based clustering using Bayesian parsimonious Gaussian mixture models. MCMC (Markov chain Monte Carlo) are used for parameter estimation. The RJMCMC (Reversible-jump Markov chain Monte Carlo) is used for model selection. GREEN et al. (1995) .


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("bpgmm")

1.0.5 by Yaoxiang Li, 4 months ago


Browse source code at https://github.com/cran/bpgmm


Authors: Xiang Lu <Xiang_Lu at urmc.rochester.edu> , Yaoxiang Li <yl814 at georgetown.edu> , Tanzy Love <tanzy_love at urmc.rochester.edu>


Documentation:   PDF Manual  


GPL-3 license


Imports methods, mcmcse, pgmm, mvtnorm, MASS, Rcpp, gtools, label.switching

Suggests testthat

Linking to Rcpp, RcppArmadillo

System requirements: C++11


See at CRAN