Package: survdnn 0.7.6
survdnn: Deep Neural Networks for Survival Analysis with R 'torch'
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>.
Authors:
survdnn_0.7.6.tar.gz
survdnn_0.7.6.zip(r-4.7)survdnn_0.7.6.zip(r-4.6)survdnn_0.7.6.zip(r-4.5)
survdnn_0.7.6.tgz(r-4.6-any)survdnn_0.7.6.tgz(r-4.5-any)
survdnn_0.7.6.tar.gz(r-4.7-any)survdnn_0.7.6.tar.gz(r-4.6-any)
survdnn_0.7.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
survdnn/json (API)
NEWS
| # Install 'survdnn' in R: |
| install.packages('survdnn', repos = c('https://ielbadisy.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ielbadisy/survdnn/issues
deep-neural-networkssurvival-analysis
Last updated from:154b073a18. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 193 | ||
| source / vignettes | OK | 199 | ||
| linux-release-x86_64 | OK | 174 | ||
| macos-release-arm64 | OK | 173 | ||
| macos-oldrel-arm64 | OK | 108 | ||
| windows-devel | OK | 137 | ||
| windows-release | OK | 115 | ||
| windows-oldrel | OK | 128 | ||
| wasm-release | OK | 120 |
Exports:aft_lossbrierbuild_dnncallback_early_stoppingcindex_survmatcox_l2_losscox_losscoxtime_losscv_survdnnevaluate_survdnngridsearch_survdnnibs_survmatplot_losssummarize_cv_survdnnsummarize_tune_survdnnsurvdnntune_survdnn
Dependencies:bitbit64callrclicodetoolscorocpp11descdigestdplyrfarverfurrrfuturegenericsggplot2globalsgluegtableisobandjsonlitelabelinglatticelifecyclelistenvmagrittrMatrixparallellypillarpkgconfigprocessxpspurrrR6RColorBrewerRcpprlangrsampleS7safetensorsscalessliderstringistringrsurvivaltibbletidyrtidyselecttorchutf8vctrsviridisLitewarpwithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Brier Score for Right-Censored Survival Data at a Fixed Time | brier |
| Early stopping callback for survdnn | callback_early_stopping |
| Concordance Index from a Survival Probability Matrix | cindex_survmat |
| K-Fold Cross-Validation for survdnn Models | cv_survdnn |
| Evaluate a survdnn Model Using Survival Metrics | evaluate_survdnn |
| Grid Search for survdnn Hyperparameters | gridsearch_survdnn |
| Integrated Brier Score (IBS) from a Survival Probability Matrix | ibs_survmat |
| Plot Training Loss for a survdnn Model | plot_loss |
| Plot survdnn Survival Curves using ggplot2 | plot.survdnn |
| Predict from a survdnn Model | predict.survdnn |
| Print a survdnn Model | print.survdnn |
| Summarize Cross-Validation Results from survdnn | summarize_cv_survdnn |
| Summarize survdnn Tuning Results | summarize_tune_survdnn |
| Summarize a Deep Survival Neural Network Model | summary.survdnn |
| Fit a Deep Neural Network for Survival Analysis | survdnn |
| Tune Hyperparameters for a survdnn Model via Cross-Validation | tune_survdnn |
