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 models for real, categorical, counting, functional and ranking data. This package contains the minimal R interface of the C++ 'MixtComp' library.


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Reference manual

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install.packages("RMixtCompIO")

4.0.0 by Quentin Grimonprez, 22 days 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/RMixtCompIO


Authors: Vincent Kubicki [aut] , Christophe Biernacki [aut] , Quentin Grimonprez [aut, cre] , Serge Iovleff [ctb] , Matthieu Marbac-Lourdelle [ctb] , √Čtienne Goffinet [ctb] , Patrick Patrick Wieschollek [ctb] (for CppOptimizationLibrary) , Tobias Wood [ctb] (for CppOptimizationLibrary)


Documentation:   PDF Manual  


AGPL-3 license


Imports Rcpp, doParallel, foreach

Suggests Rmixmod, blockcluster, testthat, RInside, xml2

Linking to Rcpp, RcppEigen, BH


See at CRAN