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-4.7-any)rpls_0.6.0.zip(r-4.6-any)rpls_0.6.0.zip(r-4.5-any)
rpls_0.6.0.tgz(r-4.6-any)rpls_0.6.0.tgz(r-4.5-any)
rpls_0.6.0.tar.gz(r-4.7-any)rpls_0.6.0.tar.gz(r-4.6-any)
rpls_0.6.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rpls/json (API)

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

On CRAN:

Conda:

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

1.00 score 229 downloads 3 exports 4 dependencies

Last updated from:ae2afc982d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK91
source / vignettesOK126
linux-releaseOK88
macos-releaseOK160
macos-oldrelOK195
windows-develOK121
windows-releaseOK56
windows-oldrelOK58
wasm-releaseOK77

Exports:prammlPRMramml

Dependencies:DEoptimRmvtnormpcaPProbustbase