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.

Package overview Data format used in RMixtComp Overview of MixtComp Object Using ClusVis with RMixtComp Output for Visualization Using RMixtComp with mixed and missing data

Vignettes Man pages API and functions Files

Package details
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@yahoo.fr>
License	AGPL-3
Version	4.1.4
URL	https://github.com/modal-inria/MixtComp
Package repository	View on CRAN
Installation	Install the latest version of this package by entering the following in R: `install.packages("RMixtComp")`