The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
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 |
| Reference manual: | rpls.pdf |
| 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 |
Please use the canonical form https://CRAN.R-project.org/package=rpls 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.