CRAN/E | pivmet

pivmet

Pivotal Methods for Bayesian Relabelling and k-Means Clustering

Installation

About

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).

github.com/leoegidi/pivmet
System requirements pandoc (>= 1.12.3), pandoc-citeproc

Key Metrics

Version 0.5.0
R ≥ 3.1.0
Published 2023-02-22 432 days ago
Needs compilation? no
License GPL-2
CRAN checks pivmet results

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Maintainer

Maintainer

Leonardo Egidi

legidi@units.it

Authors

Leonardo
Egidi[aut

cre

Roberta
Pappadà[aut
Francesco
Pauli[aut
Nicola
Torelli[aut

Material

README
NEWS
Reference manual
Package source

Vignettes

K-means clustering using MUS and other pivotal algorithms
Dealing with label switching: relabelling in Bayesian mixture models by pivotal units

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

pivmet archive

Depends

R ≥ 3.1.0

Imports

cluster
mclust
MASS
corpcor
runjags
rstan
bayesmix
rjags
mvtnorm
bayesplot
scales

Suggests

knitr
rmarkdown