CRAN/E | SparseBiplots

SparseBiplots

'HJ-Biplot' using Different Ways of Penalization Plotting with 'ggplot2'

Installation

About

'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.

Citation SparseBiplots citation info
github.com/mitzicubillamontilla/SparseBiplots
Bug report File report

Key Metrics

Version 4.0.1
R ≥ 3.3.0
Published 2021-10-24 519 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks SparseBiplots results

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Maintainer

Maintainer

Mitzi Isabel Cubilla-Montilla

mitzi@usal.es

Authors

Mitzi Isabel Cubilla-Montilla
Carlos Alfredo Torres-Cubilla
Purificacion Galindo Villardon
Ana Belen Nieto-Librero

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

SparseBiplots archive

Depends

R ≥ 3.3.0
ggplot2

Imports

ggrepel
gtable
rlang
stats
sparsepca
testthat