Package: flare Type: Package Title: Family of Lasso Regression Version: 1.8 Date: 2026-02-19 Authors@R: c(person(given = "Xingguo", family = "Li", role = "aut", email = "xingguo.leo@gmail.com"), person(given = "Tuo", family = "Zhao", role = c("aut", "cre"), email = "tourzhao@gatech.edu"), person(given = "Lie", family = "Wang", role = "aut"), person(given = "Xiaoming", family = "Yuan", role = "aut"), person(given = "Han", family = "Liu", role = "aut")) Depends: R (>= 2.15.0), lattice, MASS, Matrix, igraph Imports: methods Suggests: testthat (>= 3.0.0) Description: 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 . License: GPL-2 NeedsCompilation: yes Packaged: 2026-06-20 09:24:44 UTC; root Author: Xingguo Li [aut], Tuo Zhao [aut, cre], Lie Wang [aut], Xiaoming Yuan [aut], Han Liu [aut] Maintainer: Tuo Zhao Config/testthat/edition: 3 Config/pak/sysreqs: libglpk-dev libxml2-dev Repository: https://tourzhao-edu.r-universe.dev Date/Publication: 2026-02-19 14:30:02 UTC RemoteUrl: https://github.com/cran/flare RemoteRef: HEAD RemoteSha: 84c4e9f581ca3aea4670b579887a49a163fe9bfb