_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-survdnn 1.0.0
Propagated dependencies: r-torch@0.17.0 r-tidyr@1.3.2 r-tibble@3.3.1 r-survival@3.8-6 r-rsample@1.3.2 r-purrr@1.2.2 r-glue@1.8.1 r-ggplot2@4.0.3 r-dplyr@1.2.1 r-cli@3.6.6
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://CRAN.R-project.org/package=survdnn
Licenses: Expat
Build system: r
Synopsis: Deep Neural Networks for Survival Analysis with R 'torch'
Description:

This package provides deep learning models for right-censored survival data using the torch backend. Supports multiple loss functions, including Cox partial likelihood, L2-penalized Cox, time-dependent Cox, and accelerated failure time (AFT) loss. Offers a formula-based interface, built-in support for cross-validation, hyperparameter tuning, survival curve plotting, and evaluation metrics such as the C-index, Brier score, and integrated Brier score. For methodological details, see Kvamme et al. (2019) <https://www.jmlr.org/papers/v20/18-424.html>. The package is described in El Badisy (2026) <doi:10.32614/RJ-2026-008>.

Total packages: 1