linear_beta             Auxiliary function for simulatedata functions
ml_hyperparams_srf      Internal function for getting grid of
                        hyperparameters for random or grid search of
                        size = max_grid_size
print.survcompare       Print survcompare object
print.survensemble_cv   Prints trained survensemble object
simulate_crossterms     Simulated sample with survival outcomes with
                        non-linear and cross-term dependencies
simulate_linear         Simulated sample with survival outcomes with
                        linear dependencies
simulate_nonlinear      Simulated sample with survival outcomes with
                        non-linear dependencies
summary.survcompare     Summary of survcompare results
summary.survensemble_cv
                        Prints summary of a trained survensemble_cv
                        object
surv_brierscore         Calculates time-dependent Brier Score
surv_validate           Computes performance statistics for a survival
                        data given the predicted event probabilities
survcompare             Cross-validates and compares Cox Proportionate
                        Hazards and Survival Random Forest models
survcompare2            Compares two cross-validated models using
                        surv____cv functions of this package.
survcox_cv              Cross-validates Cox or CoxLasso model
survcox_predict         Computes event probabilities from a trained cox
                        model
survcox_train           Trains CoxPH using survival package, or trains
                        CoxLasso (cv.glmnet, lambda.min), and then
                        re-trains survival:coxph on non-zero predictors
survcoxlasso_train      Trains CoxLasso, using
                        cv.glmnet(s="lambda.min")
survival_prob_km        Calculates survival probability estimated by
                        Kaplan-Meier survival curve Uses polynomial
                        extrapolation in survival function space, using
                        poly(n=3)
survsrf_cv              Cross-validates Survival Random Forest
survsrf_predict         Predicts event probability by a trained
                        Survival Random Forest
survsrf_train           Fits randomForestSRC, with tuning by mtry,
                        nodedepth, and nodesize. Underlying model is by
                        Ishwaran et al(2008)
                        https://www.randomforestsrc.org/articles/survival.html
                        Ishwaran H, Kogalur UB, Blackstone EH, Lauer
                        MS. Random survival forests. The Annals of
                        Applied Statistics. 2008;2:841–60.
survsrf_tune            A repeated 3-fold CV over a hyperparameters
                        grid
survsrf_tune_single     Internal function for survsrf_tune(), performs
                        1 CV
survsrfens_cv           Cross-validates predictive performance for SRF
                        Ensemble
survsrfens_predict      Predicts event probability by a trained
                        sequential ensemble of Survival Random Forest
                        and CoxPH
survsrfens_train        Fits an ensemble of Cox-PH and Survival Random
                        Forest (SRF) with internal CV to tune SRF
                        hyperparameters.
survsrfstack_cv         Cross-validates stacked ensemble of the CoxPH
                        and Survival Random Forest models
survsrfstack_predict    Predicts event probability by a trained stacked
                        ensemble of Survival Random Forest and CoxPH
survsrfstack_train      Trains the stacked ensemble of the CoxPH and
                        Survival Random Forest
