Package: regnet
Type: Package
Title: Network-Based Regularization for Generalized Linear Models
Version: 1.0.2
Authors@R: c(
  person(given = "Jie", family = "Ren", role = c("aut", "cre"),
         email = "renjie0910@gmail.com"),
  person(given = c("Luann", "C."), family = "Jung", role = "aut"),
  person(given = "Yinhao", family = "Du", role = "aut"),
  person(given = "Cen", family = "Wu", role = "aut"),
  person(given = "Yu", family = "Jiang", role = "aut"),
  person(given = "Junhao", family = "Liu", role = "aut"))
Maintainer: Jie Ren <renjie0910@gmail.com>
Description: 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. 
Depends: R (>= 4.0.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: glmnet, stats, Rcpp, igraph, utils
URL: https://github.com/jrhub/regnet
BugReports: https://github.com/jrhub/regnet/issues
RoxygenNote: 7.3.2
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, covr
NeedsCompilation: yes
Packaged: 2025-02-09 22:39:54 UTC; 17854
Author: Jie Ren [aut, cre],
  Luann C. Jung [aut],
  Yinhao Du [aut],
  Cen Wu [aut],
  Yu Jiang [aut],
  Junhao Liu [aut]
Repository: CRAN
Date/Publication: 2025-02-10 00:00:06 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2026-01-12 20:33:43 UTC; windows
Archs: x64
