bpgmm
Bayesian Model Selection Approach for Parsimonious Gaussian Mixture 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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.1 |
rolling linux/jammy R-4.5 | bpgmm_1.1.1.tar.gz |
274.5 KiB |
1.1.1 |
rolling linux/noble R-4.5 | bpgmm_1.1.1.tar.gz |
282.9 KiB |
1.1.1 |
rolling source/ R- | bpgmm_1.1.1.tar.gz |
28.5 KiB |
1.1.1 |
latest linux/jammy R-4.5 | bpgmm_1.1.1.tar.gz |
274.5 KiB |
1.1.1 |
latest linux/noble R-4.5 | bpgmm_1.1.1.tar.gz |
282.9 KiB |
1.1.1 |
latest source/ R- | bpgmm_1.1.1.tar.gz |
28.5 KiB |
1.1.1 |
2026-04-26 source/ R- | bpgmm_1.1.1.tar.gz |
28.5 KiB |
1.1.1 |
2026-04-23 source/ R- | bpgmm_1.1.1.tar.gz |
28.5 KiB |
1.1.1 |
2026-04-09 windows/windows R-4.5 | bpgmm_1.1.1.zip |
680.2 KiB |
1.0.9 |
2025-04-20 source/ R- | bpgmm_1.0.9.tar.gz |
37.2 KiB |