Package: regnet
Type: Package
Title: Network-Based Regularization for Generalized Linear Models
Version: 0.4.0
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>). Two recent additions are the robust network 
    regularization for the survival response and the network regularization for continuous 
    response. Functions for other regularization methods will be included in the forthcoming 
    upgraded versions. 
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: glmnet, stats, Rcpp
URL: https://github.com/jrhub/regnet
BugReports: https://github.com/jrhub/regnet/issues
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2019-06-07 22:03:33 UTC; JieRen
Repository: CRAN
Date/Publication: 2019-06-08 14:30:02 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 05:43:13 UTC; windows
Archs: i386, x64
