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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 |
| 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.
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