glmgraph (1.0.3)
Graph-Constrained Regularization for Sparse Generalized Linear Models.
http://cran.r-project.org/web/packages/glmgraph
We propose to use sparse regression model to achieve variable selection while accounting for graph-constraints among coefficients. Different linear combination of a sparsity penalty(L1) and a smoothness(MCP) penalty has been used, which induces both sparsity of the solution and certain smoothness on the linear coefficients.
Maintainer:
Li Chen
Author(s): Li Chen, Jun Chen
License: GPL-2
Uses: Rcpp
Released over 4 years ago.
