vscc: Variable Selection for Clustering and Classification

Performs variable selection/feature reduction under a clustering or classification framework. In particular, it can be used in an automated fashion using mixture model-based methods ('teigen' and 'mclust' are currently supported). Can account for mixtures of non-Gaussian distributions via Manly transform (via 'ManlyMix'). See Andrews and McNicholas (2014) <doi:10.1007/s00357-013-9139-2> and Neal and McNicholas (2023) <doi:10.48550/arXiv.2305.16464>.

Version:	0.7
Depends:	ManlyMix
Imports:	teigen, mclust, MixGHD
Published:	2023-10-17
DOI:	10.32614/CRAN.package.vscc
Author:	Jeffrey L. Andrews [aut], Mackenzie R. Neal [aut], Paul D. McNicholas [aut, cre]
Maintainer:	Paul D. McNicholas <mcnicholas at math.mcmaster.ca>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
Citation:	vscc citation info
Materials:	ChangeLog
CRAN checks:	vscc results

Documentation:

Reference manual:

vscc.pdf

Downloads:

Package source:	vscc_0.7.tar.gz
Windows binaries:	r-devel: vscc_0.7.zip, r-release: vscc_0.7.zip, r-oldrel: vscc_0.7.zip
macOS binaries:	r-release (arm64): vscc_0.7.tgz, r-oldrel (arm64): vscc_0.7.tgz, r-release (x86_64): vscc_0.7.tgz, r-oldrel (x86_64): vscc_0.7.tgz
Old sources:	vscc archive

Linking:

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