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mcclust: Process an MCMC Sample of Clusterings

Implements methods for processing a sample of (hard) clusterings, e.g. the MCMC output of a Bayesian clustering model. Among them are methods that find a single best clustering to represent the sample, which are based on the posterior similarity matrix or a relabelling algorithm.

Version: 1.0.1
Depends: R (≥ 2.10), lpSolve
Published: 2022-05-02
DOI: 10.32614/CRAN.package.mcclust
Author: Arno Fritsch
Maintainer: Arno Fritsch <arno.fritsch at tu-dortmund.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: Cluster
CRAN checks: mcclust results

Documentation:

Reference manual: mcclust.pdf

Downloads:

Package source: mcclust_1.0.1.tar.gz
Windows binaries: r-devel: mcclust_1.0.1.zip, r-release: mcclust_1.0.1.zip, r-oldrel: mcclust_1.0.1.zip
macOS binaries: r-release (arm64): mcclust_1.0.1.tgz, r-oldrel (arm64): mcclust_1.0.1.tgz, r-release (x86_64): mcclust_1.0.1.tgz, r-oldrel (x86_64): mcclust_1.0.1.tgz
Old sources: mcclust archive

Reverse dependencies:

Reverse depends: BClustLonG, BCSub, CSclone
Reverse imports: AntMAN, clustAnalytics, MitoHEAR, multilink, semiArtificial
Reverse suggests: IMIFA, mixdir, tip

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.