flare: Family of Lasso Regression

Provides implementations of a family of Lasso variants, including Dantzig Selector, LAD Lasso, SQRT Lasso, and Lq Lasso, for estimating high-dimensional sparse linear models. We adopt the alternating direction method of multipliers and convert the original optimization problem into a sequence of L1-penalized least-squares minimization problems that are efficiently solved by linearization and multi-stage screening. In addition to sparse linear model estimation, we provide extensions of these methods to sparse Gaussian graphical model estimation, including TIGER and CLIME, using either L1 or adaptive penalties. Missing values can be tolerated for Dantzig selector and CLIME. Computation is memory-optimized using sparse matrix output. For more information, see <https://www.jmlr.org/papers/volume16/li15a/li15a.pdf>.

Version:	1.8
Depends:	R (≥ 2.15.0), lattice, MASS, Matrix, igraph
Imports:	methods
Suggests:	testthat (≥ 3.0.0)
Published:	2026-02-19
DOI:	10.32614/CRAN.package.flare
Author:	Xingguo Li [aut], Tuo Zhao [aut, cre], Lie Wang [aut], Xiaoming Yuan [aut], Han Liu [aut]
Maintainer:	Tuo Zhao <tourzhao at gatech.edu>
License:	GPL-2
NeedsCompilation:	yes
Materials:	README
In views:	MissingData
CRAN checks:	flare results

Documentation:

Reference manual:	flare.html , flare.pdf
Vignettes:	vignette (source)

Downloads:

Package source:	flare_1.8.tar.gz
Windows binaries:	r-devel: flare_1.7.0.2.zip, r-release: flare_1.7.0.2.zip, r-oldrel: flare_1.7.0.2.zip
macOS binaries:	r-release (arm64): flare_1.8.tgz, r-oldrel (arm64): flare_1.8.tgz, r-release (x86_64): flare_1.7.0.2.tgz, r-oldrel (x86_64): flare_1.7.0.2.tgz
Old sources:	flare archive

Reverse dependencies:

Reverse depends:	DNetFinder
Reverse imports:	PFLR, SHT
Reverse suggests:	CompareCausalNetworks, mcb, SHAPBoost

Linking:

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