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 |
Reference manual: | mcclust.pdf |
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 depends: | BClustLonG, BCSub, CSclone |
Reverse imports: | AntMAN, clustAnalytics, MitoHEAR, multilink, semiArtificial |
Reverse suggests: | IMIFA, mixdir, tip |
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