'HJ-Biplot' is a multivariate method that allow represent multivariate data on a subspace of low dimension, in such a way that most of the variability of the information is captured in a few dimensions. This package implements three new techniques and constructs in each case the 'HJ-Biplot', adapting restrictions to reduce weights and / or produce zero weights in the dimensions, based on the regularization theories. It implements three methods of regularization: Ridge, LASSO and Elastic Net.
Version: | 4.0.1 |
Depends: | R (≥ 3.3.0), ggplot2 |
Imports: | ggrepel, gtable, rlang, stats, sparsepca, testthat |
Published: | 2021-10-24 |
DOI: | 10.32614/CRAN.package.SparseBiplots |
Author: | Mitzi Isabel Cubilla-Montilla, Carlos Alfredo Torres-Cubilla, Purificacion Galindo Villardon and Ana Belen Nieto-Librero |
Maintainer: | Mitzi Isabel Cubilla-Montilla <mitzi at usal.es> |
BugReports: | https://github.com/mitzicubillamontilla/SparseBiplots/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/mitzicubillamontilla/SparseBiplots |
NeedsCompilation: | no |
Citation: | SparseBiplots citation info |
CRAN checks: | SparseBiplots results |
Reference manual: | SparseBiplots.pdf |
Package source: | SparseBiplots_4.0.1.tar.gz |
Windows binaries: | r-devel: SparseBiplots_4.0.1.zip, r-release: SparseBiplots_4.0.1.zip, r-oldrel: SparseBiplots_4.0.1.zip |
macOS binaries: | r-release (arm64): SparseBiplots_4.0.1.tgz, r-oldrel (arm64): SparseBiplots_4.0.1.tgz, r-release (x86_64): SparseBiplots_4.0.1.tgz, r-oldrel (x86_64): SparseBiplots_4.0.1.tgz |
Old sources: | SparseBiplots archive |
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