Fit the Regularized Gehan Estimator with Elastic Net and Sparse Group Lasso Penalties

Documentation for package ‘penAFT’ version 0.3.0

penAFT-package	Fit and tune the a semiparameteric accelerated failure time model with weight elastic net or weighted sparse group-lasso penalties.
genSurvData	Generate a survival dataset from the log-logistic accelerated failure time model.
penAFT	Fit the solution path for the regularized semiparametric accelerated failure time model with weighted elastic net or weighted sparse group lasso penalties.
penAFT.coef	Extract regression coefficients from fitted model object
penAFT.cv	Cross-validation function for fitting a regularized semiparametric accelerated failure time model
penAFT.plot	Plot cross-validation curves
penAFT.predict	Obtain linear predictor for new subjects using fitted model from 'penAFT' or 'penAFT.cv'
penAFT.trace	Print trace plot for the regularized Gehan estimator fit using 'penAFT' or 'penAFT.cv'