Package: sNPLS 1.0.40

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.

Authors:David Hervas

sNPLS_1.0.40.tar.gz
sNPLS_1.0.40.zip(r-4.7-any)sNPLS_1.0.40.zip(r-4.6-any)sNPLS_1.0.40.zip(r-4.5-any)
sNPLS_1.0.40.tgz(r-4.6-any)sNPLS_1.0.40.tgz(r-4.5-any)
sNPLS_1.0.40.tar.gz(r-4.7-any)sNPLS_1.0.40.tar.gz(r-4.6-any)
sNPLS_1.0.40.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
sNPLS/json (API)

# Install 'sNPLS' in R:
install.packages('sNPLS', repos = c('https://david-hervas.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/david-hervas/snpls/issues

Datasets:

On CRAN:

Conda:

2.70 score 10 scripts 312 downloads 7 exports 49 dependencies

Last updated from:373054a149. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE104
source / vignettesOK249
linux-releaseNOTE106
macos-releaseNOTE170
macos-oldrelNOTE139
windows-develNOTE67
windows-releaseNOTE110
windows-oldrelNOTE66
wasm-releaseOK105

Exports:auroccv_fitcv_snplsga_snplsrepeat_cvsNPLSSR

Dependencies:beeswarmcliclickRcodetoolscpp11crayondigestfarverFNNforeachfuturefuture.applyGAggplot2ggrepelglobalsgluegtableisobanditeratorskernlabKernSmoothkslabelinglatticelifecyclelistenvMASSMatrixmclustmgcvmulticoolmvtnormnlmeparallellypbapplypracmapROCR6RColorBrewerRcppRcppArmadillorlangS7scalesstringdistvctrsviridisLitewithr