survML: Flexible Estimation of Conditional Survival Functions Using Machine Learning

Tools for flexible estimation of conditional survival functions using off-the-shelf machine learning tools. Implements both global and local survival stacking. See Wolock CJ, Gilbert PB, Simon N, and Carone M (2022+) <arXiv:2211.03031>.

Version: 1.0.0
Depends: SuperLearner (≥ 2.0.28)
Imports: Iso (≥ 0.0.18.1)
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), ggplot2 (≥ 3.4.0)
Published: 2023-07-08
Author: Charles Wolock ORCID iD [aut, cre, cph]
Maintainer: Charles Wolock <cwolock at gmail.com>
BugReports: https://github.com/cwolock/survML/issues
License: GPL (≥ 3)
URL: https://github.com/cwolock/survML
NeedsCompilation: no
Materials: README NEWS
CRAN checks: survML results

Documentation:

Reference manual: survML.pdf
Vignettes: Basic Usage of survML

Downloads:

Package source: survML_1.0.0.tar.gz
Windows binaries: r-devel: survML_1.0.0.zip, r-release: survML_1.0.0.zip, r-oldrel: survML_1.0.0.zip
macOS binaries: r-release (arm64): survML_1.0.0.tgz, r-oldrel (arm64): survML_1.0.0.tgz, r-release (x86_64): survML_1.0.0.tgz, r-oldrel (x86_64): survML_1.0.0.tgz

Reverse dependencies:

Reverse imports: vaccine

Linking:

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