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RMixtComp: Mixture Models with Heterogeneous and (Partially) Missing Data

Mixture Composer (Biernacki (2015) <https://inria.hal.science/hal-01253393v1>) is a project to perform clustering using mixture models with heterogeneous data and partially missing data. Mixture models are fitted using a SEM algorithm. It includes 8 models for real, categorical, counting, functional and ranking data.

Version: 4.1.4
Depends: RMixtCompUtilities (≥ 4.1.4), R (≥ 3.5.0)
Imports: RMixtCompIO (≥ 4.0.4), ggplot2, plotly, scales
Suggests: testthat, xml2, Rmixmod, knitr, ClusVis, rmarkdown
Published: 2023-06-18
DOI: 10.32614/CRAN.package.RMixtComp
Author: Vincent Kubicki [aut], Christophe Biernacki [aut], Quentin Grimonprez [aut, cre], Matthieu Marbac-Lourdelle [ctb], Étienne Goffinet [ctb], Serge Iovleff [ctb], Julien Vandaele [ctb]
Maintainer: Quentin Grimonprez <quentingrim at yahoo.fr>
BugReports: https://github.com/modal-inria/MixtComp/issues
License: AGPL-3
Copyright: Inria - Université de Lille - CNRS
URL: https://github.com/modal-inria/MixtComp
NeedsCompilation: no
Materials: NEWS
In views: Cluster, MissingData
CRAN checks: RMixtComp results

Documentation:

Reference manual: RMixtComp.pdf
Vignettes: Using ClusVis with RMixtComp Output for Visualization
Using RMixtComp with mixed and missing data
Data format used in RMixtComp
Overview of MixtComp Object

Downloads:

Package source: RMixtComp_4.1.4.tar.gz
Windows binaries: r-devel: RMixtComp_4.1.4.zip, r-release: RMixtComp_4.1.4.zip, r-oldrel: RMixtComp_4.1.4.zip
macOS binaries: r-release (arm64): RMixtComp_4.1.4.tgz, r-oldrel (arm64): RMixtComp_4.1.4.tgz, r-release (x86_64): RMixtComp_4.1.4.tgz, r-oldrel (x86_64): RMixtComp_4.1.4.tgz
Old sources: RMixtComp archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=RMixtComp to link to this page.

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.
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