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sNPLS  

NPLS Regression with L1 Penalization
View on CRAN: Click here


Download and install sNPLS package within the R console
Install from CRAN:
install.packages("sNPLS")

Install from Github:
library("remotes")
install_github("cran/sNPLS")

Install by package version:
library("remotes")
install_version("sNPLS", "1.0.27")



Attach the package and use:
library("sNPLS")
Maintained by
David Hervas
[Scholar Profile | Author Map]
First Published: 2016-10-09
Latest Update: 2020-12-16
Description:
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.
How to cite:
David Hervas (2016). sNPLS: NPLS Regression with L1 Penalization. R package version 1.0.27, https://cran.r-project.org/web/packages/sNPLS. Accessed 21 Apr. 2025.
Previous versions and publish date:
0.1.1 (2016-10-09 13:06), 0.1.3 (2016-11-08 00:57), 0.1.4 (2016-12-27 11:58), 0.1.5 (2017-03-05 08:47), 0.1.8 (2017-05-08 00:50), 0.2.0 (2017-07-22 18:59), 0.2.7 (2017-10-01 00:44), 0.3.0 (2017-10-29 11:39), 0.3.31 (2018-02-20 18:30)
Other packages that cited sNPLS R package
View sNPLS citation profile
Other R packages that sNPLS depends, imports, suggests or enhances
Complete documentation for sNPLS
Functions, R codes and Examples using the sNPLS R package
Some associated functions: Rmatrix . SR . bread . coef.sNPLS . cv_fit . cv_snpls . fitted.sNPLS . plot.cvsNPLS . plot.repeatcv . plot.sNPLS . plot_T . plot_U . plot_Wj . plot_Wk . plot_time . plot_variables . predict.sNPLS . repeat_cv . sNPLS . summary.sNPLS . unfold3w . 
Some associated R codes: bread-data.R . sNPLS_fit.R .  Full sNPLS package functions and examples
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