It implements a new procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data (Grimonprez et al. (2018) <https://hal.inria.fr/hal-01857242>).
| Version: | 0.6.1 |
| Imports: | gglasso, MASS, Matrix, fastcluster, FactoMineR, parallelDist |
| Published: | 2020-01-16 |
| Author: | Quentin Grimonprez [aut, cre], Samuel Blanck [ctb], Alain Celisse [ths], Guillemette Marot [ths], Yi Yang [ctb], Hui Zou [ctb] |
| Maintainer: | Quentin Grimonprez <quentin.grimonprez at inria.fr> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Copyright: | Inria |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | MLGL results |
| Reference manual: | MLGL.pdf |
| Package source: | MLGL_0.6.1.tar.gz |
| Windows binaries: | r-devel: MLGL_0.6.1.zip, r-release: MLGL_0.6.1.zip, r-oldrel: MLGL_0.6.1.zip |
| macOS binaries: | r-release: MLGL_0.6.1.tgz, r-oldrel: MLGL_0.6.1.tgz |
| Old sources: | MLGL archive |
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