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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "flare" in publications use:'
type: software
license: GPL-2.0-only
title: 'flare: Family of Lasso Regression'
version: '1.8'
doi: 10.32614/CRAN.package.flare
abstract: 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>.
authors:
- family-names: Li
  given-names: Xingguo
  email: xingguo.leo@gmail.com
- family-names: Zhao
  given-names: Tuo
  email: tourzhao@gatech.edu
- family-names: Wang
  given-names: Lie
- family-names: Yuan
  given-names: Xiaoming
- family-names: Liu
  given-names: Han
repository: https://tourzhao-edu.r-universe.dev
commit: 84c4e9f581ca3aea4670b579887a49a163fe9bfb
date-released: '2026-02-19'
contact:
- family-names: Zhao
  given-names: Tuo
  email: tourzhao@gatech.edu