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>.
Version: 1.0.9 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) LinkingTo: Rcpp, RcppArmadillo Suggests: testthat Published: 2022-06-01 DOI: 10.32614/CRAN.package.bpgmm Author: Xiang Lu <Xiang_Lu at urmc.rochester.edu>, Yaoxiang Li <yl814 at georgetown.edu>, Tanzy Love <tanzy_love at urmc.rochester.edu> Maintainer: Yaoxiang Li <yl814 at georgetown.edu> License: GPL-3 NeedsCompilation: yes SystemRequirements: C++11 CRAN checks: bpgmm results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=bpgmm to link to this page.
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