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.
Version: 0.6.0 Imports: pcaPP, robustbase Published: 2020-05-07 DOI: 10.32614/CRAN.package.rpls Author: Peter Filzmoser, Sukru Acitas, Birdal Senoglu and Maximilian Plattner Maintainer: Peter Filzmoser <peter.filzmoser at tuwien.ac.at> License: GPL (≥ 3) NeedsCompilation: no CRAN checks: rpls results Documentation: Reference manual: rpls.pdf Downloads: Package source: rpls_0.6.0.tar.gz Windows binaries: r-devel: rpls_0.6.0.zip, r-release: rpls_0.6.0.zip, r-oldrel: rpls_0.6.0.zip macOS binaries: r-release (arm64): rpls_0.6.0.tgz, r-oldrel (arm64): rpls_0.6.0.tgz, r-release (x86_64): rpls_0.6.0.tgz, r-oldrel (x86_64): rpls_0.6.0.tgz Old sources: rpls archive Linking:Please use the canonical form https://CRAN.R-project.org/package=rpls to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4