msaenet

msaenet implements the multi-step adaptive elastic-net (MSAENet) algorithm for feature selection in high-dimensional regressions proposed in Xiao and Xu (2015) <DOI:10.1080/00949655.2015.1016944> (PDF).

Multi-step adaptive estimation based on MCP-net or SCAD-net is also supported.

Paper Citation

Formatted citation:

Nan Xiao and Qing-Song Xu. (2015). Multi-step adaptive elastic-net: reducing false positives in high-dimensional variable selection. Journal of Statistical Computation and Simulation 85(18), 3755-3765.

BibTeX entry:

@article{xiao2015msaenet,
  title={Multi-step adaptive elastic-net: reducing false positives in high-dimensional variable selection},
  author={Xiao, Nan and Xu, Qing-Song},
  journal={Journal of Statistical Computation and Simulation},
  volume={85},
  number={18},
  pages={3755--3765},
  year={2015},
  publisher={Taylor \& Francis}
}

Gallery

Adaptive Elastic-Net / Multi-Step Adaptive Elastic-Net

Adaptive MCP-Net / Multi-Step Adaptive MCP-Net

Adaptive SCAD-Net / Multi-Step Adaptive SCAD-Net

Installation

To download and install msaenet from CRAN:

install.packages("msaenet")

Or try the development version on GitHub:

# install.packages("devtools")
devtools::install_github("road2stat/msaenet")

Browse the package vignette (can be opened with vignette("msaenet") in R) for a quick-start.

Visit the website for more documentation.