Package: pivmet 0.6.0

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>.

Authors:Leonardo Egidi[aut, cre], Roberta Pappadà[aut], Francesco Pauli[aut], Nicola Torelli[aut]

pivmet_0.6.0.tar.gz
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pivmet_0.6.0.tgz(r-4.6-any)pivmet_0.6.0.tgz(r-4.5-any)
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pivmet_0.6.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
pivmet/json (API)

# Install 'pivmet' in R:
install.packages('pivmet', repos = c('https://leoegidi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/leoegidi/pivmet/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

jagscpp

5.23 score 6 stars 28 scripts 626 downloads 7 exports 67 dependencies

Last updated from:b24582227a. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE239
source / vignettesOK293
linux-release-x86_64NOTE227
macos-release-arm64NOTE242
macos-oldrel-arm64NOTE131
windows-develNOTE211
windows-releaseNOTE185
windows-oldrelNOTE177
wasm-releaseOK148

Exports:MUSpiv_KMeanspiv_MCMCpiv_plotpiv_relpiv_selpiv_sim

Dependencies:abindbackportsbayesmixbayesplotBHcallrcheckmatecliclustercodacorpcorcpp11descdistributionaldplyrfarvergenericsggplot2ggridgesgluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSmatrixStatsmclustmvtnormnumDerivotelpillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rjagsrlangrstanrunjagsS7scalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr

Dealing with label switching: relabelling in Bayesian mixture models by pivotal units
Example: bivariate Gaussian data | Example: fishery data | References
Rendered fromRelabelling_in_Bayesian_mixtures_by_pivotal_units.Rmdusingknitr::rmarkdown

Last update: 2023-02-22
Started: 2018-08-25

K-means clustering using MUS and other pivotal algorithms
Pivotal algorithms: how they works, and why | piv_KMeans: k-means clustering via pivotal units | References
Rendered fromK-means_clustering_using_the_MUS_algorithm.Rmdusingknitr::rmarkdown

Last update: 2021-04-28
Started: 2018-08-27