Package: APML0
Type: Package
Title: Augmented and Penalized Minimization Method L0
Version: 0.11
Date: 2026-06-13
Authors@R: c(
    person("Xiang", "Li", email = "spiritcoke@gmail.com", role = c("aut", "cre")),
    person("Shanghong", "Xie", role = "aut"),
    person("Donglin", "Zeng", role = "aut"),
    person("Yuanjia", "Wang", role = "aut"))
Description: Fit linear, logistic and Cox models regularized with L0, lasso
    (L1), elastic-net (L1 and L2), or net (L1 and Laplacian) penalty, and
    their adaptive forms, such as adaptive lasso / elastic-net and net
    adjusting for signs of linked coefficients. It solves the L0 penalty
    problem by simultaneously selecting regularization parameters and
    performing hard-thresholding or selecting the number of non-zeros. This
    augmented and penalized minimization method provides an approximation
    solution to the L0 penalty problem, but runs as fast as L1 regularization.
    The package uses a one-step coordinate descent algorithm and runs extremely
    fast by taking into account the sparsity structure of coefficients. It can
    handle very high dimensional data and has superior selection performance.
License: GPL (>= 2)
Encoding: UTF-8
Language: en-US
URL: https://github.com/LeeSprite/APML0
BugReports: https://github.com/LeeSprite/APML0/issues
Imports: Rcpp (>= 0.12.12)
LinkingTo: Rcpp, RcppEigen
Depends: Matrix (>= 1.2-10)
NeedsCompilation: yes
Packaged: 2026-06-13 17:36:05 UTC; spiri
Author: Xiang Li [aut, cre],
  Shanghong Xie [aut],
  Donglin Zeng [aut],
  Yuanjia Wang [aut]
Maintainer: Xiang Li <spiritcoke@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-19 16:00:07 UTC
Built: R 4.5.2; x86_64-apple-darwin20; 2026-06-19 19:36:03 UTC; unix
Archs: APML0.so.dSYM
