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sgPLS
View on CRAN: Click
here
Download and install sgPLS package within the R console
Install from CRAN:
install.packages("sgPLS")
Install from Github:
library("remotes")
install_github("cran/sgPLS") Install by package version:
library("remotes")
install_version("sgPLS", "1.8.1") Attach the package and use:
library("sgPLS")
Maintained by
Benoit Liquet
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-02-10
Latest Update: 2025-09-03
Description:
Regularized version of partial least square approaches providing sparse, group, and sparse group versions of partial least square regression models (Liquet, B., Lafaye de Micheaux, P., Hejblum B., Thiebaut, R. (2016) ). Version of PLS Discriminant analysis is also provided.
How to cite:
Benoit Liquet (2015). sgPLS: Sparse Group Partial Least Square Methods. R package version 1.8.1, https://cran.r-project.org/web/packages/sgPLS. Accessed 06 Jun. 2026.
Previous versions and publish date:
Other packages that cited sgPLS R package
View sgPLS citation profile
Other R packages that sgPLS depends,
imports, suggests or enhances
Complete documentation for sgPLS
Functions, R codes and Examples using
the sgPLS R package
Some associated functions: gPLS . gPLSda . per.variance . perf . plotcim . predict . sPLS . sPLSda . select.sgpls . select.spls . sgPLS-internal . sgPLS-package . sgPLS . sgPLSda . simuData . tuning.gPLS.X . tuning.sPLS.X . tuning.sgPLS.X .
Some associated R codes: gPLS.R . gPLSda.R . per.variance.R . perf.R . plotcim.R . predict.R . sPLS.R . sPLSda.R . select.sgpls.R . select.spls.R . sgPLS-internal.R . sgPLS.R . sgplsda.R . tuning.gPLS.X.R . tuning.sPLS.X.R . tuning.sgPLS.X.R . Full sgPLS package functions and examples
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