Package: pivmet 0.6.0

Leonardo Egidi

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
pivmet_0.6.0.zip(r-4.7-any)pivmet_0.6.0.zip(r-4.6-any)
pivmet_0.6.0.tar.gz(r-4.7-any)pivmet_0.6.0.tar.gz(r-4.6-any)
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://cran.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

3.45 score 28 scripts 456 downloads 7 exports 69 dependencies

Last updated from:2503fcace7. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develOK226
source / vignettesOK274
linux-releaseOK282
windows-develOK134
windows-releaseOK158
wasm-releaseOK130

Exports:MUSpiv_KMeanspiv_MCMCpiv_plotpiv_relpiv_selpiv_sim

Dependencies:abindbackportsbayesmixbayesplotBHcallrcheckmatecliclustercodacorpcorcpp11descdistributionaldplyrfarvergenericsggdistggplot2ggridgesgluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSmatrixStatsmclustmvtnormnumDerivotelpillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrquadprogQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rjagsrlangrstanrunjagsS7scalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr

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: 2018-11-19

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: 2021-04-30
Started: 2018-11-19