Network-Based Regularization for Generalized Linear Models R package regnet version 1.0.2 CRAN Task View: Omics (https://CRAN.R-project.org/view=Omics) 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. Software Depends: R (>= 4.0.0) Imports: glmnet, stats, Rcpp, igraph, utils LinkingTo: Rcpp, RcppArmadillo Suggests: testthat, covr Jie Ren <renjie0910@gmail.com> Comprehensive R Archive Network (CRAN) Jie Ren [aut, cre], Luann C. Jung [aut], Yinhao Du [aut], Cen Wu [aut], Yu Jiang [aut], Junhao Liu [aut] GPL-2 2025-02-10 application/tgz https://CRAN.R-project.org/package=regnet doi:10.32614/CRAN.package.regnet