Discriminant analysis and data clustering methods for high dimensional data, based on the assumption that high-dimensional data live in different subspaces with low dimensionality proposing a new parametrization of the Gaussian mixture model which combines the ideas of dimension reduction and constraints on the model.
| Version: | 2.2.0 |
| Depends: | grDevices, utils, graphics, stats, MASS |
| Imports: | rARPACK |
| Published: | 2019-11-19 |
| Author: | Laurent Berge, Charles Bouveyron and Stephane Girard |
| Maintainer: | Laurent Berge <laurent.berge at uni.lu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Citation: | HDclassif citation info |
| Materials: | NEWS ChangeLog |
| In views: | Cluster |
| CRAN checks: | HDclassif results |
| Reference manual: | HDclassif.pdf |
| Package source: | HDclassif_2.2.0.tar.gz |
| Windows binaries: | r-devel: HDclassif_2.2.0.zip, r-release: HDclassif_2.2.0.zip, r-oldrel: HDclassif_2.2.0.zip |
| macOS binaries: | r-release (arm64): HDclassif_2.2.0.tgz, r-oldrel (arm64): HDclassif_2.2.0.tgz, r-release (x86_64): HDclassif_2.2.0.tgz, r-oldrel (x86_64): HDclassif_2.2.0.tgz |
| Old sources: | HDclassif archive |
| Reverse suggests: | FCPS, fscaret |
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