[aut],
Adrian E. Raftery [aut],
Luca Scrucca [aut, cre]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 [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_2.3.3.tar.gz |
| Windows binaries: | r-devel: 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 |
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