Augmented and Penalized Minimization Method L0 R package APML0 version 0.11 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. Software Depends: Matrix (>= 1.2-10) Imports: Rcpp (>= 0.12.12) LinkingTo: Rcpp, RcppEigen Xiang Li <spiritcoke@gmail.com> Comprehensive R Archive Network (CRAN) Xiang Li [aut, cre], Shanghong Xie [aut], Donglin Zeng [aut], Yuanjia Wang [aut] GPL (>= 2) 2026-06-19 application/tgz https://CRAN.R-project.org/package=APML0 doi:10.32614/CRAN.package.APML0 en-US