Random Hazard Forests

Random Hazard Forests (RHF) extend Random Survival Forests (RSF) by directly estimating the hazard function and by accommodating time-dependent covariates through counting-process style inputs. The package fits tree ensembles for dynamic survival prediction, returning hazard, cumulative hazard, integrated hazard, and related performance summaries for training and test data. The methods build on Random Survival Forests described by Ishwaran et al. (2008) and on nonparametric hazard modeling with time-dependent covariates described by Lee et al. (2021) .