Clustering and Classification using Model-Based Mixture Models

Algorithms and methods for model-based clustering and classification. It supports various types of data: continuous, categorical and counting and can handle mixed data of these types. It can fit Gaussian (with diagonal covariance structure), gamma, categorical and Poisson models. The algorithms also support missing values. This package can be used as an independent alternative to the (not free) 'mixtcomp' software available at <>.


Reference manual

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1.4.2 by Serge Iovleff, a year ago

Browse source code at

Authors: Serge Iovleff [aut, cre] , Parmeet Bathia [ctb]

Documentation:   PDF Manual  

Task views: Cluster Analysis & Finite Mixture Models

GPL (>= 2) license

Imports methods

Depends on rtkore

Linking to Rcpp, rtkore

System requirements: GNU make

See at CRAN