Augmented and Penalized Minimization Method L0

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 L0 penalty problem by simultaneously selecting regularization parameters and the number of non-zero coefficients. This augmented and penalized minimization method provides an approximation solution to the L0 penalty problem, but runs as fast as L1 regularization problem. The package uses one-step coordinate descent algorithm and runs extremely fast by taking into account the sparsity structure of coefficients. It could deal with very high dimensional data and has superior selection performance.


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install.packages("APML0")

0.5 by Xiang Li, 2 months ago


Browse source code at https://github.com/cran/APML0


Authors: Xiang Li, Shanghong Xie, Donglin Zeng and Yuanjia Wang


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp

Depends on Matrix

Linking to Rcpp, RcppEigen


See at CRAN