A unified algorithm for the non-convex penalized estimation: The ncpen package
Computation
2018-11-14 v1
Abstract
Various R packages have been developed for the non-convex penalized estimation but they can only be applied to the smoothly clipped absolute deviation (SCAD) or minimax concave penalty (MCP). We develop an R package, entitled ncpen, for the non-convex penalized estimation in order to make data analysts to experience other non-convex penalties. The package ncpen implements a unified algorithm based on the convex concave procedure and modified local quadratic approximation algorithm, which can be applied to a broader range of non-convex penalties, including the SCAD and MCP as special examples. Many user-friendly functionalities such as generalized information criteria, cross-validation and L2-stabilization are provided also.
Cite
@article{arxiv.1811.05061,
title = {A unified algorithm for the non-convex penalized estimation: The ncpen package},
author = {Dongshin Kim and Sangin Lee and Sunghoon Kwon},
journal= {arXiv preprint arXiv:1811.05061},
year = {2018}
}