Two partially supervised mixture modeling methods: soft-label and belief-based modeling are implemented. For completeness, we equipped the package also with the functionality of unsupervised, semi- and fully supervised mixture modeling. The package can be applied also to selection of the best-fitting from a set of models with different component numbers or constraints on their structures. For detailed introduction see: Przemyslaw Biecek, Ewa Szczurek, Martin Vingron, Jerzy Tiuryn (2012), The R Package bgmm: Mixture Modeling with Uncertain Knowledge, Journal of Statistical Software .

Documentation

Manual: bgmm.pdf
Vignette: None available.

Maintainer: Przemyslaw Biecek <Przemyslaw.Biecek at gmail.com>

Author(s): Przemyslaw Biecek \& Ewa Szczurek

Install package and any missing dependencies by running this line in your R console:

install.packages("bgmm")

Depends R (>= 2.0), mvtnorm, car, lattice, combinat
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Package bgmm
Materials
URL http://bgmm.molgen.mpg.de/
Task Views Cluster
Version 1.8.3
Published 2017-02-27
License GPL-3
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NeedsCompilation no
Citation
CRAN checks bgmm check results
Package source bgmm_1.8.3.tar.gz