SGL-package: Fit a GLM (or cox model) with a combination of lasso and...

In wrbrooks/SGL: Fit a GLM (or cox model) with a combination of lasso and group lasso regularization

Description

Fit a regularized generalized linear model via penalized maximum likelihood. The model is fit for a path of values of the penalty parameter. Fits linear, logistic and Cox models.

Details

Package:	SGL
Type:	Package
Version:	1.0
Date:	2012-3-12
License:	GPL
LazyLoad:	yes

Only 4 functions: SGL cvSGL predictSGL plot.cvSGL

Author(s)

Noah Simon, Jerome Friedman, Trevor Hastie, and Rob Tibshirani

Maintainer: Noah Simon <[e-mail]>

References

Simon, N., Friedman, J., Hastie T., and Tibshirani, R. (2011) A Sparse-Group Lasso,
http://www-stat.stanford.edu/~nsimon/SGL.pdf

wrbrooks/SGL documentation built on May 4, 2019, 10:57 a.m.