Package: rpls 0.6.0

rpls: Robust Partial Least Squares

A robust Partial Least-Squares (PLS) method is implemented that is robust to outliers in the residuals as well as to leverage points. A specific weighting scheme is applied which avoids iterations, and leads to a highly efficient robust PLS estimator.

Authors:Peter Filzmoser, Sukru Acitas, Birdal Senoglu and Maximilian Plattner

rpls_0.6.0.tar.gz
rpls_0.6.0.zip(r-4.5)rpls_0.6.0.zip(r-4.4)rpls_0.6.0.zip(r-4.3)
rpls_0.6.0.tgz(r-4.4-any)rpls_0.6.0.tgz(r-4.3-any)
rpls_0.6.0.tar.gz(r-4.5-noble)rpls_0.6.0.tar.gz(r-4.4-noble)
rpls_0.6.0.tgz(r-4.4-emscripten)rpls_0.6.0.tgz(r-4.3-emscripten)
rpls.pdf |rpls.html✨
rpls/json (API)

# Install 'rpls' in R:

install.packages('rpls', repos = c('https://filzmoserp.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 118 downloads 3 exports 4 dependencies

Last updated 5 years agofrom:ae2afc982d. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 25 2024
R-4.5-win	OK	Oct 25 2024
R-4.5-linux	OK	Oct 25 2024
R-4.4-win	OK	Oct 25 2024
R-4.4-mac	OK	Oct 25 2024
R-4.3-win	OK	Oct 25 2024
R-4.3-mac	OK	Oct 25 2024