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.


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Reference manual

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install.packages("RMixtComp")

4.1.2 by Quentin Grimonprez, 5 months ago


https://github.com/modal-inria/MixtComp, https://massiccc.lille.inria.fr/


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, cre] , Matthieu Marbac-Lourdelle [ctb] , √Čtienne Goffinet [ctb] , Serge Iovleff [ctb]


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, markdown


See at CRAN