A Unified Algorithm for the Non-Convex Penalized Estimation: The ncpen Package

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.

Dongshin Kim (Pepperdine Graziadio Business School) , Sangin Lee (Department of Information and Statistics) , Sunghoon Kwon (Department of Applied Statistics)
2021-01-14

Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2021-003.zip

References

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Citation

For attribution, please cite this work as

Kim, et al., "A Unified Algorithm for the Non-Convex Penalized Estimation: The ncpen Package", The R Journal, 2021

BibTeX citation

@article{RJ-2021-003,
  author = {Kim, Dongshin and Lee, Sangin and Kwon, Sunghoon},
  title = {A Unified Algorithm for the Non-Convex Penalized Estimation: The ncpen Package},
  journal = {The R Journal},
  year = {2021},
  note = {https://doi.org/10.32614/RJ-2021-003},
  doi = {10.32614/RJ-2021-003},
  volume = {12},
  issue = {2},
  issn = {2073-4859},
  pages = {120-133}
}