Package: survkl 1.0.2

Yubo Shao

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>.

Authors:Yubo Shao [aut, cre], Lingfeng Luo [aut], Xiaohan Liu [aut], Junyi Qiu [aut], Di Wang [aut], Kevin He [aut]

survkl_1.0.2.tar.gz
survkl_1.0.2.zip(r-4.7-x86_64)survkl_1.0.2.zip(r-4.7-arm64)survkl_1.0.2.zip(r-4.6-x86_64)survkl_1.0.2.zip(r-4.6-arm64)survkl_1.0.2.zip(r-4.5-x86_64)
survkl_1.0.2.tgz(r-4.6-x86_64)survkl_1.0.2.tgz(r-4.6-arm64)survkl_1.0.2.tgz(r-4.5-x86_64)survkl_1.0.2.tgz(r-4.5-arm64)
survkl_1.0.2.tar.gz(r-4.7-arm64)survkl_1.0.2.tar.gz(r-4.7-x86_64)survkl_1.0.2.tar.gz(r-4.6-arm64)survkl_1.0.2.tar.gz(r-4.6-x86_64)
survkl_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
survkl/json (API)

# Install 'survkl' in R:
install.packages('survkl', repos = c('https://um-kevinhe.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/um-kevinhe/survkl/issues

Pkgdown/docs site:https://um-kevinhe.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

openblascppopenmp

5.52 score 331 downloads 11 exports 22 dependencies

Last updated from:6d9d776f7f. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK154
linux-devel-x86_64OK156
source / vignettesOK438
linux-release-arm64OK144
linux-release-x86_64OK214
macos-release-arm64OK208
macos-release-x86_64OK244
macos-oldrel-arm64OK124
macos-oldrel-x86_64OK468
windows-devel-arm64OK368
windows-devel-x86_64OK198
windows-release-arm64OK380
windows-release-x86_64OK159
windows-oldrel-x86_64OK160
wasm-releaseOK136

Exports:cal_surv_probcoxklcoxkl_enetcoxkl_ridgecv.coxklcv.coxkl_enetcv.coxkl_ridgecv.plotgenerate_etaloss_fntest_eval

Dependencies:clicowplotcpp11farverggplot2gluegtableisobandlabelinglatticelifecycleMatrixR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsviridisLitewithr

Methods for Transfer-learning Based Integrated Cox Models
Cox Proportional Hazards Model for the Target Cohort | External Summary Information | Partial Likelihood-Based Transfer Learning | Regularization for High-Dimensional Data
Rendered fromMethods.Rmdusingknitr::rmarkdown

Last update: 2026-06-06
Started: 2025-12-09

survkl: Transfer-Learning Based Integrated Cox Models
Introduction | Key Features | Installation | Quick Start | Low-Dimensional Integration | Example data structure | High-Dimensional Integration (Ridge, Elastic Net, and LASSO) | High-dimensional example data | Ridge-Penalized KL-Integrated Cox Model (coxkl_ridge) | Elastic-Net / LASSO KL-Integrated Cox Model (coxkl_enet)
Rendered fromsurvkl.Rmdusingknitr::rmarkdown

Last update: 2026-06-06
Started: 2025-12-09

Readme and manuals

Help Manual

Help pageTopics
Calculate Survival Probabilitiescal_surv_prob
Extract Coefficients from a 'coxkl' Objectcoef.coxkl
Extract Coefficients from a 'coxkl_enet' Objectcoef.coxkl_enet
Extract Coefficients from a 'coxkl_ridge' Objectcoef.coxkl_ridge
Cox Proportional Hazards Model with KL Divergence for Data Integrationcoxkl
Cox Proportional Hazards Model with KL Divergence for Data Integration and Lasso & Elastic Net Penaltycoxkl_enet
Cox Proportional Hazards Model with Ridge Penalty and External Informationcoxkl_ridge
Cross-Validated Selection of Integration Parameter ('eta') for the Cox–KL Modelcv.coxkl
Cross-Validation for CoxKL Model with elastic net & lasso penaltycv.coxkl_enet
Cross-Validation for CoxKL Ridge Model (eta tuning)cv.coxkl_ridge
Plot Cross-Validation Results vs Etacv.plot
Example high-dimensional survival dataExampleData_highdim
Example low-dimensional survival dataExampleData_lowdim
Generate a Sequence of Tuning Parameters (eta)generate_eta
Calculate the Log-Partial Likelihood for a Stratified Cox Modelloss_fn
Plot Model Performance vs Eta for 'coxkl'plot.coxkl
Plot Model Performance vs Lambda for 'coxkl_enet'plot.coxkl_enet
Plot Model Performance vs Lambda for 'coxkl_ridge'plot.coxkl_ridge
Predict Linear Predictors from a 'coxkl' Objectpredict.coxkl
Predict Linear Predictors from a coxkl_enet Objectpredict.coxkl_enet
Predict Linear Predictors from a coxkl_ridge Objectpredict.coxkl_ridge
Study to Understand Prognoses Preferences Outcomes and Risks of Treatmentsupport
Evaluate model performance on test datatest_eval