Nested Cross-Validation to Compare Cox-PH, Cox-Lasso, Survival Random Forests

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Documentation for package ‘survcompare’ version 0.2.0

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"_PACKAGE" Cross-validates and compares Cox Proportionate Hazards and Survival Random Forest models
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
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.
survcoxlasso_train Trains CoxLasso, using cv.glmnet(s="lambda.min")
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
survival_prob_km Calculates survival probability estimated by Kaplan-Meier survival curve Uses polynomial extrapolation in survival function space, using poly(n=3)
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
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
surv_brierscore Calculates time-dependent Brier Score
surv_validate Computes performance statistics for a survival data given the predicted event probabilities