Mixture Models with Heterogeneous and (Partially) Missing Data R package RMixtComp version 4.1.5 CRAN Task View: Cluster (https://CRAN.R-project.org/view=Cluster) CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData) 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. Software Depends: RMixtCompUtilities (>= 4.1.4), R (>= 3.5.0) Imports: RMixtCompIO(>= 4.0.4), ggplot2, plotly, scales Suggests: testthat, xml2, Rmixmod, knitr, rmarkdown Quentin Grimonprez <quentingrim@yahoo.fr> Comprehensive R Archive Network (CRAN) Vincent Kubicki [aut], Christophe Biernacki [aut], Quentin Grimonprez [aut, cre], Matthieu Marbac-Lourdelle [ctb], Étienne Goffinet [ctb], Serge Iovleff [ctb], Julien Vandaele [ctb] AGPL-3 2025-06-15 application/tgz https://CRAN.R-project.org/package=RMixtComp doi:10.32614/CRAN.package.RMixtComp