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DESCRIPTION
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Package: survivalmodels
Title: Models for Survival Analysis
Version: 0.1.19
Authors@R:
c(person(given = "Raphael",
family = "Sonabend",
role = c("aut", "cre"),
email = "[email protected]",
comment = c(ORCID = "0000-0001-9225-4654")),
person(given = "John",
family = "Zobolas",
role = c("aut"),
email = "[email protected]",
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' <https://CRAN.R-project.org/package=distr6>. 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>. Novel machine learning survival models wil be included in the package in near-future updates. Neural networks are implemented from the 'Python' package 'pycox' <https://github.com/havakv/pycox> and are detailed by Kvamme et al. (2019) <https://jmlr.org/papers/v20/18-424.html>. The 'Akritas' estimator is defined in Akritas (1994) <doi:10.1214/aos/1176325630>. 'DNNSurv' is defined in Zhao and Feng (2020) <arXiv:1908.02337>.
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