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bpgmm  

Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models
View on CRAN: Click here


Download and install bpgmm package within the R console
Install from CRAN:
install.packages("bpgmm")

Install from Github:
library("remotes")
install_github("cran/bpgmm")

Install by package version:
library("remotes")
install_version("bpgmm", "1.1.1")



Attach the package and use:
library("bpgmm")
Maintained by
Yaoxiang Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-02
Latest Update: 2022-06-01
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) .
How to cite:
Yaoxiang Li (2019). bpgmm: Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models. R package version 1.1.1, https://cran.r-project.org/web/packages/bpgmm. Accessed 25 Jun. 2026.
Previous versions and publish date:
1.0.5 (2019-08-02 12:00), 1.0.7 (2020-05-19 08:40), 1.0.8 (2022-05-30 08:50), 1.0.9 (2022-06-01 12:20), 1.1.1 (2025-10-30 16:40)
Other packages that cited bpgmm R package
View bpgmm citation profile
Other R packages that bpgmm depends, imports, suggests or enhances
Complete documentation for bpgmm
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