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: | 2.3.1 |
Depends: | R (≥ 3.2), mclust (≥ 5.3), BMA (≥ 3.18), foreach, iterators |
Imports: | stats, Matrix |
Suggests: | MASS, parallel, doParallel, knitr (≥ 1.12), rmarkdown (≥ 0.9) |
Published: | 2017-07-07 |
Author: | Nema Dean [aut], Adrian E. Raftery [aut], Luca Scrucca [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 |
Reference manual: | clustvarsel.pdf |
Vignettes: |
A quick tour of clustvarsel |
Package source: | clustvarsel_2.3.1.tar.gz |
Windows binaries: | r-devel: clustvarsel_2.3.1.zip, r-release: clustvarsel_2.3.1.zip, r-oldrel: clustvarsel_2.3.1.zip |
OS X El Capitan binaries: | r-release: clustvarsel_2.3.1.tgz |
OS X Mavericks binaries: | r-oldrel: clustvarsel_2.3.1.tgz |
Old sources: | clustvarsel archive |
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