R: A Unified Framework for Machine Learning Ensembles in Survival Analysis

# A Unified Framework for Machine Learning Ensembles in Survival Analysis

## Documentation for package ‘SuperSurv’ version 0.1.7

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

censor_weights | Access SuperSurv ensemble weights
censor_weights.SuperSurv | Access SuperSurv ensemble weights
coef.SuperSurv | Extract SuperSurv ensemble coefficients
estimate_marginal_rmst | Estimate an Adjusted Marginal RMST Contrast
eval_brier | IPCW Brier Score and Integrated Brier Score (IBS)
eval_cindex | Calculate Concordance Index (Harrell's or Uno's)
eval_summary | Evaluate SuperSurv predictions on test data
eval_timeROC | Time-Dependent AUC and Integrated AUC
eval_times | Access SuperSurv prediction evaluation times
eval_times.SuperSurv | Access SuperSurv prediction evaluation times
event_weights | Access SuperSurv ensemble weights
event_weights.SuperSurv | Access SuperSurv ensemble weights
explain_kernel | Explain Predictions with Global SHAP (Kernel SHAP)
explain_survex | Create a Time-Dependent Survex Explainer
learner_names | Access SuperSurv learner names
learner_names.SuperSurv | Access SuperSurv learner names
list_wrappers | List Available Wrappers and Screeners in SuperSurv
metabric | METABRIC Breast Cancer Dataset
plot_beeswarm | Beeswarm Summary Plot for SuperSurv SHAP
plot_benchmark | Plot Longitudinal Benchmark Metrics
plot_calibration | Plot Survival Calibration Curve
plot_dependence | Plot SHAP Dependence for SuperSurv
plot_global_importance | Plot Global Feature Importance for SuperSurv
plot_marginal_rmst_curve | Plot Adjusted Marginal RMST Contrast Over Time
plot_patient_waterfall | Waterfall Plot for an Individual Patient
plot_predict | Plot Predicted Survival Curves
plot_rmst_vs_obs | Plot Predicted RMST vs. Observed Survival Times
plot_survival_heatmap | Survival Probability Heatmap
predict.SuperSurv | Predict method for SuperSurv fits
print.summary.SuperSurv | Summarize a SuperSurv fit
print.SuperSurv | Print a SuperSurv fit
screen.all | Keep All Variables Screener
screen.elasticnet | Elastic Net Screening Algorithm
screen.glmnet | GLMNET (Lasso) Screening
screen.marg | Marginal Cox Regression Screening
screen.rfsrc | Random Survival Forest Screening Algorithm
screen.var | High Variance Screening Algorithm (Unsupervised)
selected_variables | Access variables selected by SuperSurv screeners
selected_variables.SuperSurv | Access variables selected by SuperSurv screeners
summary.SuperSurv | Summarize a SuperSurv fit
SuperSurv | Super Learner for conditional survival functions
surv.aorsf | Wrapper for AORSF (Oblique Random Survival Forest)
surv.bart | Wrapper for BART (Bayesian Additive Regression Trees)
surv.coxboost | Wrapper function for Component-Wise Boosting (CoxBoost)
surv.coxph | Wrapper for standard Cox Proportional Hazards
surv.exponential | Parametric Survival Prediction Wrapper (Exponential)
surv.gam | Wrapper for Generalized Additive Cox Regression (GAM)
surv.gbm | Wrapper function for Gradient Boosting (GBM) prediction algorithm
surv.glmnet | Wrapper function for Penalized Cox Regression (GLMNET)
surv.km | Kaplan-Meier Prediction Algorithm
surv.loglogistic | Parametric Survival Prediction Wrapper (Log-Logistic)
surv.lognormal | Parametric Survival Prediction Wrapper (Log-Normal)
surv.parametric | Universal Parametric Survival Wrapper
surv.ranger | Wrapper function for Ranger Random Survival Forest
surv.rfsrc | Wrapper function for Random Survival Forests (RFSRC)
surv.ridge | Wrapper for Ridge Regression (Penalized Cox)
surv.rpart | Wrapper for Survival Regression Trees (rpart)
surv.svm | Wrapper for Survival Support Vector Machine (survivalsvm)
surv.weibull | Parametric Survival Prediction Wrapper (Weibull)
surv.xgboost | Wrapper for XGBoost (Robust CV-Tuned + Safe Prediction)
training_variables | Access SuperSurv training variable names
training_variables.SuperSurv | Access SuperSurv training variable names