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msaenet implements the multi-step adaptive elastic-net (MSAENet)algorithm for feature selection in high-dimensional regressions proposedin Xiao and Xu (2015) [PDF].

Nonconvex multi-step adaptive estimations based on MCP-net or SCAD-netare also supported.

Checkvignette("msaenet") to get started.

You can install msaenet from CRAN:

install.packages("msaenet")

Or try the development version on GitHub:

remotes::install_github("nanxstats/msaenet")

To cite the msaenet package in publications, please use

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.

A BibTeX entry for LaTeX users is

@article{xiao2015multi,title   ={Multi-step adaptive elastic-net: reducing false positives in high-dimensional variable selection},author  ={Nan Xiao and Qing-Song Xu},journal ={Journal of Statistical Computation and Simulation},volume  ={85},number  ={18},pages   ={3755--3765},year    ={2015},doi     ={10.1080/00949655.2015.1016944}}

To contribute to this project, please take a look at theContributingGuidelines first. Pleasenote that the msaenet project is released with aContributor Code ofConduct. By contributingto this project, you agree to abide by its terms.

msaenet is free and open source software, licensed under GPL-3.