SparseBiplots: 'HJ Biplot' using Different Ways of Penalization

Contains a set of functions that allow to represent multivariate on a subspace of low dimension, in such a way that most of the variability of the information is captured. This representation is carried out through the 'HJ Biplot' methodology. A first method performs the 'HJ Biplot'.Then, the package implements three new techniques and constructs in each case the 'HJ Biplot', adapting restrictions to contract and / or produce zero charges in the main components, using three methods of regularization: Ridge, LASSO and Elastic Net.

Version: 3.5.0
Imports: sparsepca
Published: 2019-07-02
Author: Mitzi Cubilla-Montilla, Carlos Torres, Ana Belen Nieto Librero and Purificacion Galindo Villardon
Maintainer: Mitzi Cubilla-Montilla <mitzi at usal.es>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: SparseBiplots results

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Reference manual: SparseBiplots.pdf
Package source: SparseBiplots_3.5.0.tar.gz
Windows binaries: r-devel: SparseBiplots_3.5.0.zip, r-release: SparseBiplots_3.5.0.zip, r-oldrel: SparseBiplots_3.5.0.zip
OS X binaries: r-release: SparseBiplots_3.5.0.tgz, r-oldrel: SparseBiplots_3.5.0.tgz

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