clustvarsel: Variable Selection for Model-Based Clustering

A function which implements variable selection methodology for model-based clustering which 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 parallelization is also available.

Version: 2.1
Depends: R (≥ 2.15), mclust (≥ 4.4), BMA (≥ 3.16), foreach, iterators
Suggests: MASS, parallel, doParallel
Published: 2014-10-15
Author: Nema Dean, Adrian E. Raftery, and Luca Scrucca
Maintainer: Luca Scrucca <luca at stat.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
Package source: clustvarsel_2.1.tar.gz
Windows binaries: r-devel: clustvarsel_2.1.zip, r-release: clustvarsel_2.1.zip, r-oldrel: clustvarsel_2.1.zip
OS X Snow Leopard binaries: r-release: clustvarsel_2.1.tgz, r-oldrel: clustvarsel_2.1.tgz
OS X Mavericks binaries: r-release: not available
Old sources: clustvarsel archive