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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: 2022-09-08
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

Documentation:

Reference manual: L2E.pdf
Vignettes: Introduction to the L2E Package

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:

Please use the canonical form https://CRAN.R-project.org/package=L2E 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.