pivmet: Pivotal Methods for Bayesian Relabelling and k-Means Clustering

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: 0.5.0
Depends: R (≥ 3.1.0)
Imports: cluster, mclust, MASS, corpcor, runjags, rstan, bayesmix, rjags, mvtnorm, bayesplot, scales
Suggests: knitr, rmarkdown
Published: 2023-02-22
Author: Leonardo Egidi[aut, cre], Roberta Pappadà[aut], Francesco Pauli[aut], Nicola Torelli[aut]
Maintainer: Leonardo Egidi <legidi at units.it>
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

Documentation:

Reference manual: pivmet.pdf
Vignettes: K-means clustering using MUS and other pivotal algorithms
Dealing with label switching: relabelling in Bayesian mixture models by pivotal units

Downloads:

Package source: pivmet_0.5.0.tar.gz
Windows binaries: r-devel: pivmet_0.5.0.zip, r-release: pivmet_0.5.0.zip, r-oldrel: pivmet_0.5.0.zip
macOS binaries: r-release (arm64): pivmet_0.5.0.tgz, r-oldrel (arm64): pivmet_0.5.0.tgz, r-release (x86_64): pivmet_0.5.0.tgz
Old sources: pivmet archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=pivmet to link to this page.