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
Depends:	R (≥ 2.10), lpSolve
Published:	2012-07-23
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.tar.gz
Windows binaries:	r-devel: mcclust_1.0.zip, r-release: mcclust_1.0.zip, r-oldrel: mcclust_1.0.zip
macOS binaries:	r-release (arm64): mcclust_1.0.tgz, r-oldrel (arm64): mcclust_1.0.tgz, r-release (x86_64): mcclust_1.0.tgz, r-oldrel (x86_64): mcclust_1.0.tgz

Reverse dependencies:

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

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