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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 |
Reference manual: | sNPLS.pdf |
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 |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.