pivmet: Pivotal Methods for Bayesian Relabelling and k-Means Clustering (original) (raw)
Collection of pivotal algorithms for: relabelling the MCMC chains in order to undo the label switching problem in Bayesian mixture models; fitting sparse finite mixtures; initializing the centers of the classical k-means algorithm in order to obtain a better clustering solution. For further details see Egidi, Pappadà, Pauli and Torelli (2018b)ISBN:9788891910233.
| Version: | 0.6.0 |
|---|---|
| Depends: | R (≥ 3.1.0) |
| Imports: | cluster, mclust, MASS, corpcor, runjags, rstan, bayesmix, rjags, mvtnorm, bayesplot, scales |
| Suggests: | knitr, rmarkdown, testthat |
| Published: | 2024-05-30 |
| DOI: | 10.32614/CRAN.package.pivmet |
| Author: | Leonardo Egidi[aut, cre], Roberta Pappadà[aut], Francesco Pauli[aut], Nicola Torelli[aut] |
| Maintainer: | Leonardo Egidi |
| License: | GPL-2 |
| URL: | https://github.com/leoegidi/pivmet |
| NeedsCompilation: | no |
| SystemRequirements: | pandoc (>= 1.12.3), pandoc-citeproc |
| Materials: | README NEWS |
| CRAN checks: | pivmet results |
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