MixAll: Clustering and Classification using Model-Based Mixture Models

Algorithms and methods for model-based clustering and classification. It supports various types of data: continuous, categorical and counting and can handle mixed data of these types. It can fit Gaussian (with diagonal covariance structure), gamma, categorical and Poisson models. The algorithms also support missing values. This package can be used as an independent alternative to the (not free) 'mixtcomp' software available at <https://massiccc.lille.inria.fr/>.

Version: 1.5.1
Depends: R (≥ 3.0.2), rtkore (≥ 1.5.0)
Imports: methods
LinkingTo: Rcpp (≥ 0.11.0), rtkore (≥ 1.5.0)
Published: 2019-09-12
Author: Serge Iovleff [aut, cre], Parmeet Bathia [ctb]
Maintainer: Serge Iovleff <Serge.Iovleff at stkpp.org>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright: inria, University of Lille
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: NEWS
In views: Cluster
CRAN checks: MixAll results


Reference manual: MixAll.pdf
Vignettes: Clustering With MixAll
Learning With MixAll


Package source: MixAll_1.5.1.tar.gz
Windows binaries: r-devel: MixAll_1.5.1.zip, r-release: MixAll_1.5.1.zip, r-oldrel: MixAll_1.5.1.zip
macOS binaries: r-release (arm64): MixAll_1.5.1.tgz, r-oldrel (arm64): MixAll_1.5.1.tgz, r-release (x86_64): MixAll_1.5.1.tgz, r-oldrel (x86_64): MixAll_1.5.1.tgz
Old sources: MixAll archive

Reverse dependencies:

Reverse imports: AZIAD


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