bpgmm: Bayesian Model Selection Approach for Parsimonious GaussianMixture 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) <doi:10.1093/biomet/82.4.711>.
| Version: | 1.1.1 |
| 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: | 2025-10-30 |
| DOI: | 10.32614/CRAN.package.bpgmm |
| Author: | Yaoxiang Li [aut, cre], Xiang Lu [aut], Tanzy Love [aut] |
| Maintainer: | Yaoxiang Li <yl814 at georgetown.edu> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | bpgmm results |
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