# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "penAFT" in publications use:' type: software license: GPL-2.0-or-later title: 'penAFT: Fit the Semiparameteric Accelerated Failure Time Model with Elastic Net and Sparse Group Lasso Penalties' version: 0.3.2 doi: 10.32614/CRAN.package.penAFT abstract: 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 . authors: - family-names: Molstad given-names: Aaron J. email: amolstad@ufl.edu orcid: https://orcid.org/0000-0003-0645-5105 - family-names: Suder given-names: Piotr M. repository: https://ajmolstad.r-universe.dev repository-code: https://github.com/ajmolstad/penAFT commit: edf51c94f6c202547e828fb517732bd1309f86d3 url: https://ajmolstad.github.io/research/ date-released: '2024-12-03' contact: - family-names: Molstad given-names: Aaron J. email: amolstad@ufl.edu orcid: https://orcid.org/0000-0003-0645-5105