NPLS Regression with L1 Penalization
Coefficients from a sNPLS model
Internal function for cv_snpls
Cross-validation for a sNPLS model
Fitted method for sNPLS models
Plot cross validation results for sNPLS objects
Density plot for repeat_cv results
Plots for sNPLS model fits
Internal function for plot.sNPLS
Internal function for plot.sNPLS
Internal function for plot.sNPLS
Internal function for plot.sNPLS
Internal function for plot.sNPLS
Internal function for plot.sNPLS
Predict for sNPLS models
Repeated cross-validation for sNPLS models
R-matrix from a sNPLS model fit
Fit a sNPLS model
Compute Selectivity Ratio for a sNPLS model
Summary for sNPLS models
Unfolding of three-way arrays
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.