Links[{"label":"SuperSurv.html","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/refman/SuperSurv.html"},{"label":"SuperSurv.pdf","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/SuperSurv.pdf"},{"label":"06. Machine Learning with Random Survival Forests","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/base-learner-rfsrc.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/base-learner-rfsrc.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/base-learner-rfsrc.R"},{"label":"09. Causal Effects and Adjusted Marginal Contrasts (RMST)","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/causal-rmst.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/causal-rmst.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/causal-rmst.R"},{"label":"11. Extending SuperSurv","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/extending-supersurv.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/extending-supersurv.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/extending-supersurv.R"},{"label":"05. Advanced Hyperparameter Tuning \u0026 Grid Search","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/grid-search.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/grid-search.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/grid-search.R"},{"label":"00. Installation \u0026 Setup","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/installation.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/installation.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/installation.R"},{"label":"02. Model Performance \u0026 Benchmarking","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/model-performance.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/model-performance.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/model-performance.R"}]
TextReference manual: SuperSurv.html , SuperSurv.pdf Vignettes: 06. Machine Learning with Random Survival Forests ( source , R code ) 09. Causal Effects and Adjusted Marginal Contrasts (RMST) ( source , R code ) 11. Extending SuperSurv ( source , R code ) 05. Advanced Hyperparameter Tuning & Grid Search ( source , R code ) 00. Installation & Setup ( source , R code ) 02. Model Performance & Benchmarking ( source , R code ) 07. Parametric Survival Models ( source , R code ) 10. Scaling Up with Parallel Processing ( source , R code ) 04. High-Dimensional Data & Variable Screening ( source , R code ) 08. Interpreting the Black Box with SHAP & survex ( source , R code ) 03. Ensemble vs. Best Model Selection ( source , R code ) 01. SuperSurv with Ensemble ( source , R code )