Performs a regularization approach to variable selection in the model-based clustering and classification frameworks. First, the variables are arranged in order with a lasso-like procedure. Second, the method of Maugis, Celeux, and Martin-Magniette (2009, 2011) is adapted to define the role of variables in the two frameworks.
| Version: | 1.1 |
| Imports: | Rcpp (≥ 0.11.1), glasso, parallel, Rmixmod, methods |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2015-09-20 |
| Author: | Mohammed Sedki, Gilles Celeux, Cathy Maugis-Rabusseau |
| Maintainer: | Mohammed Sedki <mohammed.sedki at u-psud.fr> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | SelvarMix results |
| Reference manual: | SelvarMix.pdf |
| Package source: | SelvarMix_1.1.tar.gz |
| Windows binaries: | r-devel: SelvarMix_1.1.zip, r-release: SelvarMix_1.1.zip, r-oldrel: SelvarMix_1.1.zip |
| OS X Mavericks binaries: | r-release: SelvarMix_1.1.tgz, r-oldrel: SelvarMix_1.1.tgz |
| Old sources: | SelvarMix archive |
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