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survkl: Estimate Survival Data with Data Integration

Provides flexible and efficient tools for integrating external risk scores into Cox proportional hazards models while accounting for population heterogeneity. Enables robust estimation, improved predictive accuracy, and user-friendly workflows for modern survival analysis. For more information, see Wang et al. (2023) <doi:10.48550/arXiv.2302.11123>.

Version: 1.0.0
Depends: R (≥ 4.0)
Imports: Rcpp, ggplot2, stats, cowplot, Matrix, rlang
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests: knitr, rmarkdown, survival
Published: 2026-04-21
DOI: 10.32614/CRAN.package.survkl
Author: Yubo Shao [aut, cre], Lingfeng Luo [aut], Xiaohan Liu [aut], Junyi Qiu [aut], Di Wang [aut], Kevin He [aut]
Maintainer: Yubo Shao <ybshao at umich.edu>
License: GPL-3
URL: https://um-kevinhe.github.io/survkl/
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README, NEWS
CRAN checks: survkl results

Documentation:

Reference manual: survkl.html , survkl.pdf
Vignettes: Methods for Transfer-learning Based Integrated Cox Models (source)
survkl: Transfer-Learning Based Integrated Cox Models (source, R code)

Downloads:

Package source: survkl_1.0.0.tar.gz
Windows binaries: r-release: survkl_1.0.0.zip, r-oldrel: survkl_1.0.0.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): survkl_1.0.0.tgz, r-release (x86_64): survkl_1.0.0.tgz, r-oldrel (x86_64): survkl_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=survkl to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.