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Functions to perform robust variable selection and regression using the Fast and Scalable Cellwise-Robust Ensemble (FSCRE) algorithm. The approach establishes a robust foundation using the Detect Deviating Cells (DDC) algorithm and robust correlation estimates. It then employs a competitive ensemble architecture where a robust Least Angle Regression (LARS) engine proposes candidate variables and cross-validation arbitrates their assignment. A final robust MM-estimator is applied to the selected predictors.
| Version: | 2.0.0 |
| Imports: | cellWise, robustbase, mvnfast |
| Suggests: | testthat |
| Published: | 2026-03-02 |
| DOI: | 10.32614/CRAN.package.srlars |
| Author: | Anthony Christidis [aut, cre], Gabriela Cohen-Freue [aut] |
| Maintainer: | Anthony Christidis <anthony.christidis at stat.ubc.ca> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | srlars results |
| Reference manual: | srlars.html , srlars.pdf |
| Package source: | srlars_2.0.0.tar.gz |
| Windows binaries: | r-devel: srlars_2.0.0.zip, r-release: srlars_2.0.0.zip, r-oldrel: srlars_2.0.0.zip |
| macOS binaries: | r-release (arm64): srlars_2.0.0.tgz, r-oldrel (arm64): srlars_2.0.0.tgz, r-release (x86_64): srlars_2.0.0.tgz, r-oldrel (x86_64): srlars_2.0.0.tgz |
| Old sources: | srlars archive |
| Reverse imports: | RMSS |
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These binaries (installable software) and packages are in development.
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