The R Journal: article published in 2020, volume 12:2

A Unified Algorithm for the Non-Convex Penalized Estimation: The ncpen Package PDF download
Dongshin Kim, Sangin Lee and Sunghoon Kwon , The R Journal (2020) 12:2, pages 43-60.

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 ridge regularization are provided also.

Received: 2019-02-25; online 2021-01-14, supplementary material, (4 Kb)
CRAN packages: lars, glmpath, glmnet, plus, sparsenet, cvplogit, ncvreg, ncpen, spls, Rcpp
CRAN Task Views implied by cited CRAN packages: MachineLearning, Survival, ChemPhys, HighPerformanceComputing, NumericalMathematics


CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2021-003,
  author = {Dongshin Kim and Sangin Lee and Sunghoon Kwon},
  title = {{A Unified Algorithm for the Non-Convex Penalized Estimation:
          The ncpen Package}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-003},
  url = {https://doi.org/10.32614/RJ-2021-003},
  pages = {43--60},
  volume = {12},
  number = {2}
}