R: Tools for Flexible Survival Analysis Using Machine Learning

# Tools for Flexible Survival Analysis Using Machine Learning

## Documentation for package ‘survML’ version 1.2.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

crossfit_oracle_preds | Generate cross-fitted oracle prediction function estimates
crossfit_surv_preds | Generate cross-fitted conditional survival predictions
currstatCIR | Estimate a survival function under current status sampling
DR_pseudo_outcome_regression | Generate oracle prediction function estimates using doubly-robust pseudo-outcome regression with SuperLearner
generate_folds | Generate cross-fitting and sample-splitting folds
predict.stackG | Obtain predicted conditional survival and cumulative hazard functions from a global survival stacking object
predict.stackL | Obtain predicted conditional survival function from a local survival stacking object
stackG | Estimate a conditional survival function using global survival stacking
stackL | Estimate a conditional survival function via local survival stacking
vim | Estimate AUC VIM
vim_accuracy | Estimate classification accuracy VIM
vim_AUC | Estimate AUC VIM
vim_brier | Estimate Brier score VIM
vim_cindex | Estimate concordance index VIM
vim_rsquared | Estimate R-squared (proportion of explained variance) VIM based on event occurrence by a landmark time
vim_survival_time_mse | Estimate restricted predicted survival time MSE VIM