CRAN/E | bpgmm

bpgmm

Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models

Installation

About

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) doi:10.1093/biomet/82.4.711.

System requirements C++11

Key Metrics

Version 1.0.9
R ≥ 3.1.0
Published 2022-06-01 667 days ago
Needs compilation? yes
License GPL-3
CRAN checks bpgmm results

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Maintainer

Maintainer

Yaoxiang Li

yl814@georgetown.edu

Authors

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

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

bpgmm archive

Depends

R ≥ 3.1.0

Imports

methods ≥ 3.5.1
mcmcse ≥ 1.3-2
pgmm ≥ 1.2.3
mvtnorm ≥ 1.0-10
MASS ≥ 7.3-51.1
Rcpp ≥ 1.0.1
gtools ≥ 3.8.1
label.switching ≥ 1.8
fabMix ≥ 5.0
mclust ≥ 5.4.3

Suggests

testthat

LinkingTo

Rcpp
RcppArmadillo