jrhub/regnet: Network-Based Regularization for Generalized Linear Models

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.

Getting started

Package details

AuthorJie Ren, Luann C. Jung, Yinhao Du, Cen Wu, Yu Jiang, Junhao Liu
MaintainerJie Ren <jieren@ksu.edu>
LicenseGPL-2
Version1.0.1
URL https://github.com/jrhub/regnet
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("jrhub/regnet")
jrhub/regnet documentation built on Feb. 22, 2024, 2:56 p.m.