ddsPLS: Data-Driven Sparse Partial Least Squares

A sparse Partial Least Squares implementation which uses soft-threshold estimation of the covariance matrices and therein introduces sparsity. Number of components and regularization coefficients are automatically set.

Version: 1.2.1
Depends: foreach, R (≥ 2.10)
Imports: Rcpp (≥ 1.0.5), doParallel, shiny, RColorBrewer
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, MASS
Published: 2024-01-30
DOI: 10.32614/CRAN.package.ddsPLS
Author: Hadrien Lorenzo
Maintainer: Hadrien Lorenzo <hadrien.lorenzo.2015 at>
License: MIT + file LICENSE
NeedsCompilation: yes
Citation: ddsPLS citation info
Materials: README
CRAN checks: ddsPLS results


Reference manual: ddsPLS.pdf
Vignettes: Data-Driven Sparse PLS (ddsPLS)


Package source: ddsPLS_1.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): ddsPLS_1.2.1.tgz, r-oldrel (arm64): ddsPLS_1.2.1.tgz, r-release (x86_64): ddsPLS_1.2.1.tgz, r-oldrel (x86_64): ddsPLS_1.2.1.tgz
Old sources: ddsPLS archive


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