Package: PRIMAL
Type: Package
Title: Parametric Simplex Method for Sparse Learning
Version: 1.0.3
Date: 2025-12-03
Authors@R: c(
    person(given = "Zichong", family = "Li", role = c("aut", "cre"),
           email = "zichongli5@gmail.com"),
    person(given = "Qianli", family = "Shen", role = "aut")
  )
Author: Zichong Li [aut, cre],
  Qianli Shen [aut]
Maintainer: Zichong Li <zichongli5@gmail.com>
LinkingTo: Rcpp, RcppEigen
Description: Implements a unified framework of parametric simplex method for a variety of sparse learning problems (e.g., Dantzig selector (for linear regression), sparse quantile regression, sparse support vector machines, and compressive sensing) combined with efficient hyper-parameter selection strategies. The core algorithm is implemented in C++ with Eigen3 support for portable high performance linear algebra. For more details about parametric simplex method, see Haotian Pang (2017) <https://papers.nips.cc/paper/6623-parametric-simplex-method-for-sparse-learning.pdf>.
Imports: Matrix
License: GPL (>= 2)
NeedsCompilation: yes
RoxygenNote: 6.1.1
Packaged: 2025-12-03 17:44:04 UTC; lizichong
Repository: CRAN
Date/Publication: 2025-12-03 18:10:02 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 01:35:21 UTC; unix
Archs: PRIMAL.so.dSYM
