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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 gmail.com>
License: MIT + file LICENSE
NeedsCompilation: yes
Citation: ddsPLS citation info
Materials: README
CRAN checks: ddsPLS results

Documentation:

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

Downloads:

Package source: ddsPLS_1.2.1.tar.gz
Windows binaries: r-devel: ddsPLS_1.2.1.zip, r-release: ddsPLS_1.2.1.zip, r-oldrel: ddsPLS_1.2.1.zip
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ddsPLS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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