rebmix: Finite Mixture Modeling, Clustering & Classification

Random univariate and multivariate finite mixture model generation, estimation, clustering, latent class analysis and classification. Variables can be continuous, discrete, independent or dependent and may follow normal, lognormal, Weibull, gamma, Gumbel, binomial, Poisson, Dirac, uniform or circular von Mises parametric families.

Version: 2.14.0
Depends: R (≥ 2.10)
Imports: methods, stats, utils, graphics, grDevices
Published: 2022-02-02
Author: Marko Nagode ORCID iD [aut, cre], Branislav Panic ORCID iD [ctb], Jernej Klemenc ORCID iD [ctb], Simon Oman ORCID iD [ctb]
Maintainer: Marko Nagode <marko.nagode at fs.uni-lj.si>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: rebmix citation info
Materials: NEWS
In views: Cluster
CRAN checks: rebmix results

Documentation:

Reference manual: rebmix.pdf
Vignettes: rebmix: The Rebmix Package

Downloads:

Package source: rebmix_2.14.0.tar.gz
Windows binaries: r-devel: rebmix_2.14.0.zip, r-release: rebmix_2.14.0.zip, r-oldrel: rebmix_2.14.0.zip
macOS binaries: r-release (arm64): rebmix_2.14.0.tgz, r-oldrel (arm64): rebmix_2.14.0.tgz, r-release (x86_64): rebmix_2.14.0.tgz, r-oldrel (x86_64): rebmix_2.14.0.tgz
Old sources: rebmix archive

Linking:

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