Package: penAFT
Type: Package
Title: Fit the Semiparameteric Accelerated Failure Time Model with
        Elastic Net and Sparse Group Lasso Penalties
Version: 0.3.2
Authors@R: c(person("Aaron J.", "Molstad", email = "amolstad@ufl.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0645-5105")), person("Piotr M.", "Suder", role = "aut"))
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 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>.
License: GPL (>= 2)
URL: https://ajmolstad.github.io/research/
BugReports: https://github.com/ajmolstad/penAFT/issues
Imports: Rcpp, Matrix, ggplot2, irlba
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Repository: https://ajmolstad.r-universe.dev
Date/Publication: 2024-12-03 14:51:22 UTC
RemoteUrl: https://github.com/ajmolstad/penaft
RemoteRef: HEAD
RemoteSha: edf51c94f6c202547e828fb517732bd1309f86d3
Packaged: 2026-10-11 15:49:28 UTC; root
Author: Aaron J. Molstad [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-0645-5105>),
  Piotr M. Suder [aut]
Maintainer: Aaron J. Molstad <amolstad@ufl.edu>