clustvarsel: Variable Selection for Gaussian Model-Based Clustering

Variable selection for Gaussian model-based clustering as implemented in the 'mclust' package. The methodology allows to find the (locally) optimal subset of variables in a data set that have group/cluster information. A greedy or headlong search can be used, either in a forward-backward or backward-forward direction, with or without sub-sampling at the hierarchical clustering stage for starting 'mclust' models. By default the algorithm uses a sequential search, but parallelisation is also available.

Version: 2.3.3
Depends: R (≥ 3.2), mclust (≥ 5.3)
Imports: stats, Matrix, BMA (≥ 3.18), foreach, iterators
Suggests: MASS, parallel, doParallel, knitr (≥ 1.12), rmarkdown (≥ 0.9)
Published: 2018-11-19
Author: Nema Dean ORCID iD [aut], Adrian E. Raftery [aut], Luca Scrucca ORCID iD [aut, cre]
Maintainer: Luca Scrucca <luca.scrucca at unipg.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: clustvarsel citation info
Materials: NEWS
In views: ChemPhys, Cluster, Multivariate
CRAN checks: clustvarsel results

Downloads:

Reference manual: clustvarsel.pdf
Vignettes: A quick tour of clustvarsel
Package source: clustvarsel_2.3.3.tar.gz
Windows binaries: r-devel: clustvarsel_2.3.3.zip, r-devel-gcc8: clustvarsel_2.3.3.zip, r-release: clustvarsel_2.3.3.zip, r-oldrel: clustvarsel_2.3.3.zip
OS X binaries: r-release: clustvarsel_2.3.3.tgz, r-oldrel: clustvarsel_2.3.3.tgz
Old sources: clustvarsel archive

Reverse dependencies:

Reverse depends: survtype

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