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survivalmodels  

Models for Survival Analysis
View on CRAN: Click here


Download and install survivalmodels package within the R console
Install from CRAN:
install.packages("survivalmodels")

Install from Github:
library("remotes")
install_github("cran/survivalmodels")

Install by package version:
library("remotes")
install_version("survivalmodels", "0.1.191")



Attach the package and use:
library("survivalmodels")
Maintained by
Yohann Foucher
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-10-15
Latest Update: 2024-03-19
Description:
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>.
How to cite:
Yohann Foucher (2020). survivalmodels: Models for Survival Analysis. R package version 0.1.191, https://cran.r-project.org/web/packages/survivalmodels. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:11), 0.1.0 (2020-10-15 15:30), 0.1.1 (2020-10-20 09:00), 0.1.2 (2020-11-03 11:40), 0.1.3 (2020-11-11 14:30), 0.1.4 (2020-11-18 14:40), 0.1.5 (2021-01-17 12:40), 0.1.6 (2021-02-09 13:10), 0.1.7 (2021-03-09 16:00), 0.1.8 (2021-04-17 09:10), 0.1.9 (2021-09-12 01:20), 0.1.11 (2022-02-16 08:50), 0.1.12 (2022-03-11 12:30), 0.1.13 (2022-03-24 09:40)
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