regnet: Network-Based Regularization for Generalized Linear Models
Version 0.2.0

Network-based regularization has achieved success in variable selection for high-dimensional biological data due to its ability to incorporate correlations between genomic features. This package provides procedures for fitting network-based regularization, minimax concave penalty (MCP) and lasso penalty for generalized linear models. This current version, regnet0.2.0, focuses on binary outcomes. Functions for continuous, survival outcomes and other regularization methods will be included in the forthcoming upgraded versions.

Getting started

Package details

AuthorJie Ren, Luann C. Jung, Yinhao Du, Cen Wu, Yu Jiang, Junhao Liu
Date of publication2017-10-15 03:08:32 UTC
MaintainerJie Ren <[email protected]>
Package repositoryView on CRAN
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regnet documentation built on Nov. 17, 2017, 7:03 a.m.