Package: survivalmodels 0.1.191

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>.

Authors:Raphael Sonabend [aut], Yohann Foucher [cre]

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survivalmodels.pdf |survivalmodels.html✨
survivalmodels/json (API)

# Install 'survivalmodels' in R:
install.packages('survivalmodels', repos = c('https://foucher-y.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/foucher-y/survivalmodels/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

4.39 score 33 scripts 543 downloads 21 exports 1 dependencies

Last updated 8 months agofrom:dd1db0ca58. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 16 2024
R-4.5-win-x86_64OKOct 16 2024
R-4.5-linux-x86_64OKOct 16 2024
R-4.4-win-x86_64OKOct 16 2024
R-4.4-mac-x86_64OKOct 16 2024
R-4.4-mac-aarch64OKOct 16 2024
R-4.3-win-x86_64OKOct 16 2024
R-4.3-mac-x86_64OKOct 16 2024
R-4.3-mac-aarch64OKOct 16 2024

Exports:build_keras_netbuild_pytorch_netcindexcoxtimedeephitdeepsurvget_keras_optimizerget_pycox_activationget_pycox_callbacksget_pycox_initget_pycox_optiminstall_kerasinstall_pycoxinstall_torchloghazpchazardpycox_prepare_train_datarequireNamespacesset_seedsimsurvdatasurv_to_risk

Dependencies:Rcpp