survML: Tools for Flexible Survival Analysis Using Machine Learning

Statistical tools for analyzing time-to-event data using machine learning. Implements survival stacking for conditional survival estimation, standardized survival function estimation for current status data, and methods for algorithm-agnostic variable importance. See Wolock CJ, Gilbert PB, Simon N, and Carone M (2024) <doi:10.1080/10618600.2024.2304070>.

Version:	1.2.0
Depends:	SuperLearner (≥ 2.0.28)
Imports:	Iso (≥ 0.0.18.1), haldensify (≥ 0.2.3), fdrtool (≥ 1.2.17), ChernoffDist (≥ 0.1.0), dplyr (≥ 1.0.10), gtools (≥ 3.9.5), mboost (≥ 2.9.0), survival (≥ 3.5.0), stats (≥ 4.3.2), methods (≥ 4.3.2)
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0), ggplot2 (≥ 3.4.0), gam (≥ 1.22.0)
Published:	2024-10-31
DOI:	10.32614/CRAN.package.survML
Author:	Charles Wolock [aut, cre, cph], Avi Kenny [ctb]
Maintainer:	Charles Wolock <cwolock at gmail.com>
BugReports:	https://github.com/cwolock/survML/issues
License:	GPL (≥ 3)
URL:	https://github.com/cwolock/survML, https://cwolock.github.io/survML/
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	survML results

Documentation:

Reference manual:	survML.pdf
Vignettes:	Estimating a conditional survival function using off-the-shelf machine learning tools (source, R code) Estimating a covariate-adjusted survival function using current status data (source, R code) Assessing variable importance in survival analysis using machine learning (source, R code)

Downloads:

Package source:	survML_1.2.0.tar.gz
Windows binaries:	r-devel: survML_1.2.0.zip, r-release: survML_1.2.0.zip, r-oldrel: survML_1.2.0.zip
macOS binaries:	r-release (arm64): survML_1.2.0.tgz, r-oldrel (arm64): survML_1.2.0.tgz, r-release (x86_64): survML_1.2.0.tgz, r-oldrel (x86_64): survML_1.2.0.tgz
Old sources:	survML archive

Reverse dependencies:

Reverse imports:

vaccine

Linking:

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