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.