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 |