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.
Version: 1.0.2 Depends: R (≥ 4.0.0) Imports: glmnet, stats, Rcpp, igraph, utils LinkingTo: Rcpp, RcppArmadillo Suggests: testthat, covr Published: 2025-02-10 DOI: 10.32614/CRAN.package.regnet Author: Jie Ren [aut, cre], Luann C. Jung [aut], Yinhao Du [aut], Cen Wu [aut], Yu Jiang [aut], Junhao Liu [aut] Maintainer: Jie Ren <renjie0910 at gmail.com> BugReports: https://github.com/jrhub/regnet/issues License: GPL-2 URL: https://github.com/jrhub/regnet NeedsCompilation: yes Materials: README NEWS In views: Omics CRAN checks: regnet results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=regnet to link to this page.
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