Package: bpgmm
Type: Package
Title: Bayesian Model Selection Approach for Parsimonious Gaussian
        Mixture Models
Version: 1.3.4
Date: 2026-05-28
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), parallel, Rcpp (>=
        1.0.1), gtools (>= 3.8.1), label.switching (>= 1.8), fabMix (>=
        5.0), mclust (>= 5.4.3)
Authors@R: c(
    person(given = "Yaoxiang", family = "Li",  role = c("aut","cre"),email = "liyaoxiang@outlook.com"),
    person(given = "Xiang",  family = "Lu",    role = "aut"),
    person(given = "Tanzy",  family = "Love",  role = "aut"))
Author: Yaoxiang Li [aut, cre], Xiang Lu [aut], Tanzy Love [aut]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>
Description: 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>.
License: GPL-3
URL: https://github.com/YaoxiangLi/bpgmm,
        https://yaoxiangli.github.io/bpgmm/,
        https://doi.org/10.1007/s00357-021-09391-8
BugReports: https://github.com/YaoxiangLi/bpgmm/issues
Encoding: UTF-8
RoxygenNote: 7.3.2
Suggests: knitr, rmarkdown, testthat
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Config/pak/sysreqs: cmake libfftw3-dev make libuv1-dev
Repository: https://yaoxiangli.r-universe.dev
Date/Publication: 2026-06-27 05:39:13 UTC
RemoteUrl: https://github.com/yaoxiangli/bpgmm
RemoteRef: HEAD
RemoteSha: 91d8c85a5232fc35bfa72fd4cf943b3ce5bd70fb
NeedsCompilation: yes
Packaged: 2026-06-27 07:09:44 UTC; root