sNPLS: NPLS Regression with L1 Penalization

Tools for performing variable selection in three-way data using N-PLS in combination with L1 penalization, Selectivity Ratio and VIP scores. The N-PLS model (Rasmus Bro, 1996 <doi:10.1002/(SICI)1099-128X(199601)10:1%3C47::AID-CEM400%3E3.0.CO;2-C>) is the natural extension of PLS (Partial Least Squares) to N-way structures, and tries to maximize the covariance between X and Y data arrays. The package also adds variable selection through L1 penalization, Selectivity Ratio and VIP scores.

Version:	1.0.27
Depends:	R (≥ 2.10)
Imports:	clickR, future, future.apply, ggplot2, ggrepel, ks, MASS, Matrix, pbapply
Published:	2020-12-16
DOI:	10.32614/CRAN.package.sNPLS
Author:	David Hervas
Maintainer:	David Hervas <ddhervas at yahoo.es>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
Materials:	README
CRAN checks:	sNPLS results

Documentation:

Reference manual:

sNPLS.html , sNPLS.pdf

Downloads:

Package source:	sNPLS_1.0.27.tar.gz
Windows binaries:	r-devel: sNPLS_1.0.27.zip, r-release: sNPLS_1.0.27.zip, r-oldrel: sNPLS_1.0.27.zip
macOS binaries:	r-release (arm64): sNPLS_1.0.27.tgz, r-oldrel (arm64): sNPLS_1.0.27.tgz, r-release (x86_64): sNPLS_1.0.27.tgz, r-oldrel (x86_64): sNPLS_1.0.27.tgz
Old sources:	sNPLS archive

Linking:

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