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ncpen  

Unified Algorithm for Non-Convex Penalized Estimation for Generalized Linear Models
View on CRAN: Click here


Download and install ncpen package within the R console
Install from CRAN:
install.packages("ncpen")

Install from Github:
library("remotes")
install_github("cran/ncpen")

Install by package version:
library("remotes")
install_version("ncpen", "1.0.1")



Attach the package and use:
library("ncpen")
Maintained by
Dongshin Kim
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-02-21
Latest Update: 2018-11-17
Description:
An efficient unified nonconvex penalized estimation algorithm for Gaussian (linear), binomial Logit (logistic), Poisson, multinomial Logit, and Cox proportional hazard regression models. The unified algorithm is implemented based on the convex concave procedure and the algorithm can be applied to most of the existing nonconvex penalties. The algorithm also supports convex penalty: least absolute shrinkage and selection operator (LASSO). Supported nonconvex penalties include smoothly clipped absolute deviation (SCAD), minimax concave penalty (MCP), truncated LASSO penalty (TLP), clipped LASSO (CLASSO), sparse ridge (SRIDGE), modified bridge (MBRIDGE) and modified log (MLOG). For high-dimensional data (data set with many variables), the algorithm selects relevant variables producing a parsimonious regression model. Kim, D., Lee, S. and Kwon, S. (2018) , Lee, S., Kwon, S. and Kim, Y. (2016) , Kwon, S., Lee, S. and Kim, Y. (2015) . (This research is funded by Julian Virtue Professorship from Center for Applied Research at Pepperdine Graziadio Business School and the National Research Foundation of Korea.)
How to cite:
Dongshin Kim (2018). ncpen: Unified Algorithm for Non-Convex Penalized Estimation for Generalized Linear Models. R package version 1.0.1, https://cran.r-project.org/web/packages/ncpen. Accessed 27 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:24), 0.2.0 (2018-02-21 19:36), 1.0.0 (2018-11-17 19:20)
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