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