Fit the Semiparametric Accelerated Failure Time Model with Elastic Net and Sparse Group Lasso Penalties
Overview
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 rank-based 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, Statistics in Medicine doi:10.1002/sim.9264.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-04-22
- ERROR13 OK, 1 ERROR2026-04-18
- OK14 OK2026-03-10
Documentation
- Help pages
- 8includes a package overview page
- Examples that run
- 86%6 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- not measured
- Median days to close, 50 most recently updated closed PRs
- 0
Checks run against github.com/ajmolstad/penaft on 2026-10-11.
No development-tooling practices detected in the upstream repository.
Dependencies
Installing penAFT adds 20 packages (10 with compiled code, 17 MB of source tarballs). Heaviest: ggplot2 6.0 MB, Rcpp 1.8 MB, isoband 1.5 MB.
Code & Tests
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- RR 4.2.0 released · 2022-04-22
- 0.2.02022-01-25
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2022-01-25
- Total releases
- 3 / 4 yrs
- License
- GPL (>= 2) OSI
- Download size
- 19 KB
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