stc04003/rocTree: Receiver Operating Characteristic (ROC)-Guided Classification and Survival Tree

Receiver Operating Characteristic (ROC)-guided survival trees and ensemble algorithms are implemented, providing a unified framework for tree-structured analysis with censored survival outcomes. A time-invariant partition scheme on the survivor population was considered to incorporate time-dependent covariates. Motivated by ideas of randomized tests, generalized time-dependent ROC curves were used to evaluate the performance of survival trees and establish the optimality of the target hazard/survival function. The optimality of the target hazard function motivates us to use a weighted average of the time-dependent area under the curve (AUC) on a set of time points to evaluate the prediction performance of survival trees and to guide splitting and pruning. A detailed description of the implemented methods can be found in Sun et al. (2019) <arXiv:1809.05627>.

Getting started

Package details

AuthorYifei Sun [aut], Mei-Cheng Wang [aut], Sy Han Chiou [aut, cre]
MaintainerSy Han Chiou <schiou@utdallas.edu>
LicenseGPL (>= 3)
Version1.1.1
URL http://github.com/stc04003/rocTree
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("stc04003/rocTree")
stc04003/rocTree documentation built on Sept. 25, 2020, 11:51 a.m.