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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>.

Version:0.1.191
Imports:Rcpp (≥ 1.0.5)
LinkingTo:Rcpp
Suggests:keras (≥ 2.11.0),pseudo,reticulate,survival
Published:2024-03-19
DOI:10.32614/CRAN.package.survivalmodels
Author:Raphael SonabendORCID iD [aut], Yohann FoucherORCID iD [cre]
Maintainer:Yohann Foucher <yohann.foucher at univ-poitiers.fr>
BugReports:https://github.com/foucher-y/survivalmodels/issues
License:MIT + fileLICENSE
URL:https://github.com/RaphaelS1/survivalmodels/
NeedsCompilation:yes
Materials:README
CRAN checks:survivalmodels results

Documentation:

Reference manual:survivalmodels.html ,survivalmodels.pdf

Downloads:

Package source: survivalmodels_0.1.191.tar.gz
Windows binaries: r-devel:survivalmodels_0.1.191.zip, r-release:survivalmodels_0.1.191.zip, r-oldrel:survivalmodels_0.1.191.zip
macOS binaries: r-release (arm64):survivalmodels_0.1.191.tgz, r-oldrel (arm64):survivalmodels_0.1.191.tgz, r-release (x86_64):survivalmodels_0.1.191.tgz, r-oldrel (x86_64):survivalmodels_0.1.191.tgz
Old sources: survivalmodels archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=survivalmodelsto link to this page.


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