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: | 1.0.7 |
| 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: | 2020-05-19 |
| 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 |
| Reference manual: | bpgmm.pdf |
| Package source: | bpgmm_1.0.7.tar.gz |
| Windows binaries: | r-devel: bpgmm_1.0.7.zip, r-release: bpgmm_1.0.7.zip, r-oldrel: bpgmm_1.0.7.zip |
| macOS binaries: | r-release: bpgmm_1.0.7.tgz, r-oldrel: bpgmm_1.0.7.tgz |
| Old sources: | bpgmm archive |
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