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SuperSurv
View on CRAN: Click
here
Download and install SuperSurv package within the R console
Install from CRAN:
install.packages("SuperSurv")
Install from Github:
library("remotes")
install_github("cran/SuperSurv") Install by package version:
library("remotes")
install_version("SuperSurv", "0.1.7") Attach the package and use:
library("SuperSurv")
Maintained by
Yue Lyu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-03-26
Latest Update: 2026-03-26
Description:
Implements a Super Learner framework for right-censored survival data. The package fits convex combinations of parametric, semiparametric, and machine learning survival learners by minimizing cross-validated risk using inverse probability of censoring weighting (IPCW). It provides tools for automated hyperparameter grid search, high-dimensional variable screening, and evaluation of prediction performance using metrics such as the Brier score, Uno's C-index, and time-dependent area under the curve (AUC). Additional utilities support model interpretation for survival ensembles, including Shapley additive explanations (SHAP), and estimation of covariate-adjusted restricted mean survival time (RMST) contrasts. The methodology is related to treatment-specific survival curve estimation using machine learning described by Westling, Luedtke, Gilbert and Carone (2024) <doi:10.1080/01621459.2023.2205060>, and the unified ensemble framework described in Lyu et al. (2026) <doi:10.64898/2026.03.11.711010>.
How to cite:
Yue Lyu (2026). SuperSurv: A Unified Framework for Machine Learning Ensembles in Survival Analysis. R package version 0.1.7, https://cran.r-project.org/web/packages/SuperSurv. Accessed 24 Oct. 2026.
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