'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: | 4.0.0 |
| Depends: | R (≥ 3.2), ggplot2 |
| Imports: | ggrepel, gtable, rlang, stats, sparsepca, testthat |
| Published: | 2020-06-28 |
| 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 |
| CRAN checks: | SparseBiplots results |
| Reference manual: | SparseBiplots.pdf |
| Package source: | SparseBiplots_4.0.0.tar.gz |
| Windows binaries: | r-devel: SparseBiplots_4.0.0.zip, r-release: SparseBiplots_4.0.0.zip, r-oldrel: SparseBiplots_4.0.0.zip |
| macOS binaries: | r-release: SparseBiplots_4.0.0.tgz, r-oldrel: SparseBiplots_4.0.0.tgz |
| Old sources: | SparseBiplots archive |
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