A unified algorithm for the non-convex penalized estimation: The ncpen package

TL;DR

The ncpen R package offers a unified algorithm for non-convex penalized estimation, enabling analysis with various penalties beyond SCAD and MCP, and includes user-friendly features like cross-validation and information criteria.

Contribution

It introduces a versatile R package implementing a unified algorithm for multiple non-convex penalties, expanding options for data analysts.

Findings

Supports a broader range of non-convex penalties including SCAD and MCP

Provides functionalities like cross-validation and information criteria

Demonstrates effectiveness through simulations and real data applications

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.