Package: ddsPLS 1.2.1

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.

Authors:Hadrien Lorenzo

ddsPLS_1.2.1.tar.gz
ddsPLS_1.2.1.zip(r-4.5)ddsPLS_1.2.1.zip(r-4.4)ddsPLS_1.2.1.zip(r-4.3)
ddsPLS_1.2.1.tgz(r-4.5-x86_64)ddsPLS_1.2.1.tgz(r-4.5-arm64)ddsPLS_1.2.1.tgz(r-4.4-x86_64)ddsPLS_1.2.1.tgz(r-4.4-arm64)ddsPLS_1.2.1.tgz(r-4.3-x86_64)ddsPLS_1.2.1.tgz(r-4.3-arm64)
ddsPLS_1.2.1.tar.gz(r-4.5-noble)ddsPLS_1.2.1.tar.gz(r-4.4-noble)
ddsPLS_1.2.1.tgz(r-4.4-emscripten)ddsPLS_1.2.1.tgz(r-4.3-emscripten)
ddsPLS.pdf |ddsPLS.html✨
ddsPLS/json (API)

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

Bug tracker:https://github.com/hlorenzo/ddspls/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

missing-datamulti-blockplssupervised-learningsvdvariable-selectioncpp

3.70 score 7 scripts 428 downloads 2 exports 36 dependencies

Last updated 1 years agofrom:3a57108fa0. Checks:11 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 24 2025
R-4.5-win-x86_64OKFeb 24 2025
R-4.5-mac-x86_64OKFeb 24 2025
R-4.5-mac-aarch64OKFeb 24 2025
R-4.5-linux-x86_64OKFeb 24 2025
R-4.4-win-x86_64OKFeb 24 2025
R-4.4-mac-x86_64OKFeb 24 2025
R-4.4-mac-aarch64OKFeb 24 2025
R-4.3-win-x86_64OKFeb 24 2025
R-4.3-mac-x86_64OKFeb 24 2025
R-4.3-mac-aarch64OKFeb 24 2025

Exports:ddsPLSddsPLS_App

Dependencies:base64encbslibcachemclicodetoolscommonmarkcrayondigestdoParallelfastmapfontawesomeforeachfsgluehtmltoolshttpuviteratorsjquerylibjsonlitelaterlifecyclemagrittrmemoisemimepromisesR6rappdirsRColorBrewerRcppRcppEigenrlangsassshinysourcetoolswithrxtable

Data-Driven Sparse PLS (ddsPLS)

Rendered fromddsPLS.Rmdusingknitr::rmarkdownon Feb 24 2025.

Last update: 2024-01-29
Started: 2018-07-12