Description
Fit the Regularized Gehan Estimator with Elastic Net and.
Description
The semiparametric accelerated failure time (AFT) model is an attractive alternative to the Cox proportional hazards model. This package provides a suite of functions for fitting one popular estimator of the semiparametric AFT model, the regularized Gehan estimator. Specifically, we provide functions for cross-validation, prediction, coefficient extraction, and visualizing both trace plots and cross-validation curves. For further details, please see Suder, P. M. and Molstad, A. J., (2022+) Scalable algorithms for semiparametric accelerated failure time models in high dimensions, to appear in Statistics in Medicine <doi:10.1002/sim.9264>.
README.md
penAFT
An R package for fitting semiparametric accelerated failure time models under weighted elastic net and weighted sparse group lasso penalties.
Installation
penAFT can be loaded directly into R through the the devtools package:
install.packages("devtools")
library(devtools)
devtools::install_github("ajmolstad/penAFT")
Citation
If you use this package, please cite:
Suder, PM, Molstad, AJ. Scalable algorithms for semiparametric accelerated failure time models in high dimensions. Statistics in Medicine. 2022; 1- 17. doi:10.1002/sim.9264
A bibtex entry can be downloaded directly from https://onlinelibrary.wiley.com/action/showCitFormats?doi=10.1002%2Fsim.9264.
Usage directions
See this document for details on implementation and usage.