Mixture Models with Heterogeneous and (Partially) Missing Data

Mixture Composer < https://github.com/modal-inria/MixtComp> is a project to build mixture models with heterogeneous data sets and partially missing data management. It includes 8 models for real, categorical, counting, functional and ranking data.


Reference manual

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4.1.3 by Julien Vandaele, 8 months ago


Report a bug at https://github.com/modal-inria/MixtComp/issues

Browse source code at https://github.com/cran/RMixtComp

Authors: Vincent Kubicki [aut] , Christophe Biernacki [aut] , Quentin Grimonprez [aut] , Matthieu Marbac-Lourdelle [ctb] , √Čtienne Goffinet [ctb] , Serge Iovleff [ctb] , Julien Vandaele [ctb, cre]

Documentation:   PDF Manual  

Task views: Missing Data

AGPL-3 license

Imports RMixtCompIO, ggplot2, plotly, scales

Depends on RMixtCompUtilities

Suggests testthat, xml2, Rmixmod, blockcluster, knitr, ClusVis, rmarkdown

See at CRAN