MGMM: Mutliple Clustering with Mixture Model per Blocs

Multiple model-based clustering is achieved by splitting the variables into blocks. Each block of variables is modelled by a mixture model for achieving the clustering purpose. Model selection (block repartition, number of components and number of blocks) is managed with information criteria (penalized likelihood or MICL). Parameter inference is done by maximum likelihood.

Package details

AuthorMarbac, M. and Vandewalle, V.
MaintainerMatthieu Marbac <>
LicenseGPL (>= 2)
Package repositoryView on R-Forge
Installation Install the latest version of this package by entering the following in R:
install.packages("MGMM", repos="")

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MGMM documentation built on May 2, 2019, 5:19 p.m.