Package: APML0 0.11

APML0: 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 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.

Authors:Xiang Li [aut, cre], Shanghong Xie [aut], Donglin Zeng [aut], Yuanjia Wang [aut]