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

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.

AuthorNoah Simon, Jerome Friedman, Trevor Hastie, and Rob Tibshirani
Date of publication2013-04-02 20:51:39
MaintainerNoah Simon <nsimon@stanford.edu>
LicenseGPL
Version1.1

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Files

SGL
SGL/MD5
SGL/NAMESPACE
SGL/R
SGL/R/zCoxCrossVal.R
SGL/R/zOneDim.r
SGL/R/zPathCalc.r
SGL/R/zPathCalcExact.r
SGL/R/zlogitCrossVal.R SGL/R/predictSGL.R
SGL/R/zzPathCalc.r
SGL/R/zOneDimCox.r
SGL/R/log.likelihood.calc.R SGL/R/plot.cv.SGL.R
SGL/R/zOneDimLogit.r
SGL/R/SGLmain.R SGL/R/error.bars.R SGL/R/zLinCrossVal.R
SGL/R/zfindNum.r
SGL/man
SGL/man/cvSGL.Rd SGL/man/predictSGL.Rd SGL/man/plot.cv.SGL.Rd SGL/man/SGL-package.Rd SGL/man/SGL.Rd
SGL/DESCRIPTION
SGL/src
SGL/src/Coxfit.cpp

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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