Network-based regularization has achieved success in variable selection for high-dimensional biological data due to its ability to incorporate correlations among genomic features. This package provides procedures of network-based variable selection for generalized linear models (Ren et al. (2017) <doi:10.1186/s12863-017-0495-5> and Ren et al.(2019) <doi:10.1002/gepi.22194>). Continuous, binary, and survival response are supported. Robust network-based methods are available for continuous and survival responses.
Package details | 
          |
|---|---|
| Maintainer | Jie Ren <renjie0910@gmail.com> | 
| License | GPL-2 | 
| Version | 1.0.2 | 
| URL | https://github.com/jrhub/regnet | 
| Package repository | View on GitHub | 
| Installation | 
                Install the latest version of this package by entering the following in R:
                
               | 
            
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.