Package: survivalmodels Title: Models for Survival Analysis Version: 0.1.19 Authors@R: c(person(given = "Raphael", family = "Sonabend", role = c("aut", "cre"), email = "raphaelsonabend@gmail.com", comment = c(ORCID = "0000-0001-9225-4654")), person(given = "John", family = "Zobolas", role = c("aut"), email = "bblodfon@gmail.com", comment = c(ORCID = "0000-0002-3609-8674"))) 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, survival probabilities, or survival distributions with 'distr6' . Models are either implemented from 'Python' via 'reticulate' , from code in GitHub packages, or novel implementations using 'Rcpp' . Novel machine learning survival models wil be included in the package in near-future updates. Neural networks are implemented from the 'Python' package 'pycox' and are detailed by Kvamme et al. (2019) . The 'Akritas' estimator is defined in Akritas (1994) . 'DNNSurv' is defined in Zhao and Feng (2020) . License: MIT + file LICENSE URL: https://github.com/RaphaelS1/survivalmodels/ BugReports: https://github.com/RaphaelS1/survivalmodels/issues Imports: Rcpp (>= 1.0.5) Suggests: distr6 (>= 1.6.6), keras (>= 2.11.0), param6, pseudo, reticulate, set6, survival, testthat LinkingTo: Rcpp Remotes: xoopR/distr6, xoopR/param6, xoopR/set6 Encoding: UTF-8 Roxygen: list(markdown = TRUE) RoxygenNote: 7.2.3 Repository: https://raphaels1.r-universe.dev Date/Publication: 2024-07-01 08:40:40 UTC RemoteUrl: https://github.com/RaphaelS1/survivalmodels RemoteRef: HEAD RemoteSha: e7af58c7d8aec9f253bfed9f3814308ba2952e43 NeedsCompilation: yes Packaged: 2026-10-11 09:42:28 UTC; root Author: Raphael Sonabend [aut, cre] (ORCID: ), John Zobolas [aut] (ORCID: ) Maintainer: Raphael Sonabend