L2E: Robust Structured Regression via the L2 Criterion

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年09月08日
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

Documentation:

Reference manual: L2E.html , L2E.pdf
Vignettes: Introduction to the L2E Package (source, R code)

Downloads:

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

Linking:

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