An implementation of a computational framework for performing robust structured regression with the L2 criterion from Chi and Chi (2021+). Improvements using the majorization-minimization (MM) principle from Liu, Chi, and Lange (2022+) added in Version 2.0.
| Version: | 2.0 |
| Depends: | R (≥ 3.5.0), osqp |
| Imports: | isotone, cobs, ncvreg, Matrix, signal, robustbase |
| Suggests: | knitr, rmarkdown, ggplot2, latex2exp |
| Published: | 2022-09-08 |
| DOI: | 10.32614/CRAN.package.L2E |
| Author: | Xiaoqian Liu [aut, ctb], Jocelyn Chi [aut, cre], Lisa Lin [ctb], Kenneth Lange [aut], Eric Chi [aut] |
| Maintainer: | Jocelyn Chi <jocetchi at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Citation: | L2E citation info |
| Materials: | README |
| CRAN checks: | L2E results |
| Reference manual: | L2E.html , L2E.pdf |
| Vignettes: |
Introduction to the L2E Package (source, R code) |
| Package source: | L2E_2.0.tar.gz |
| Windows binaries: | r-devel: L2E_2.0.zip, r-release: L2E_2.0.zip, r-oldrel: L2E_2.0.zip |
| macOS binaries: | r-release (arm64): L2E_2.0.tgz, r-oldrel (arm64): L2E_2.0.tgz, r-release (x86_64): L2E_2.0.tgz, r-oldrel (x86_64): L2E_2.0.tgz |
| Old sources: | L2E archive |
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