Package: regnet
Type: Package
Title: Network-Based Regularization for Generalized Linear Models
Version: 1.0.1
Author: Jie Ren, Luann C. Jung, Yinhao Du, Cen Wu, Yu Jiang, Junhao Liu
Maintainer: Jie Ren <jieren@ksu.edu>
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: 7.3.1
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, covr
NeedsCompilation: yes
Packaged: 2024-02-22 02:04:56 UTC; 17854
Repository: CRAN
Date/Publication: 2024-02-22 03:20:02 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 01:51:42 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
