survivalmodels
Models for Survival Analysis
Implementations of classical and machine learning models for survival analysis, including deep neural networks via 'keras' and 'tensorflow'. Each model includes a separated fit and predict interface with consistent prediction types for predicting risk or survival probabilities. Models are either implemented from 'Python' via 'reticulate' <https://CRAN.R-project.org/package=reticulate>, from code in GitHub packages, or novel implementations using 'Rcpp' <https://CRAN.R-project.org/package=Rcpp>. Neural networks are implemented from the 'Python' package 'pycox' <https://github.com/havakv/pycox>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.191 |
rolling linux/jammy R-4.5 | survivalmodels_0.1.191.tar.gz |
184.4 KiB |
0.1.191 |
rolling linux/noble R-4.5 | survivalmodels_0.1.191.tar.gz |
185.3 KiB |
0.1.191 |
rolling source/ R- | survivalmodels_0.1.191.tar.gz |
29.1 KiB |
0.1.191 |
latest linux/jammy R-4.5 | survivalmodels_0.1.191.tar.gz |
184.4 KiB |
0.1.191 |
latest linux/noble R-4.5 | survivalmodels_0.1.191.tar.gz |
185.3 KiB |
0.1.191 |
latest source/ R- | survivalmodels_0.1.191.tar.gz |
29.1 KiB |
0.1.191 |
2026-04-26 source/ R- | survivalmodels_0.1.191.tar.gz |
29.1 KiB |
0.1.191 |
2026-04-23 source/ R- | survivalmodels_0.1.191.tar.gz |
29.1 KiB |
0.1.191 |
2026-04-09 windows/windows R-4.5 | survivalmodels_0.1.191.zip |
506.6 KiB |
0.1.191 |
2025-04-20 source/ R- | survivalmodels_0.1.191.tar.gz |
29.1 KiB |