CRAN/E | rocTree

rocTree

Receiver Operating Characteristic (ROC)-Guided Classification and Survival Tree

Installation

About

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) .

github.com/stc04003/rocTree
Bug report File report

Key Metrics

Version 1.1.1
R ≥ 3.5.0
Published 2020-08-01 1362 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks rocTree results

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Maintainer

Maintainer

Sy Han Chiou

schiou@utdallas.edu

Authors

Yifei Sun

aut

Mei-Cheng Wang

aut

Sy Han Chiou

aut / cre

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

rocTree archive

Depends

R ≥ 3.5.0

Imports

DiagrammeR ≥ 1.0.0
data.tree ≥ 0.7.5
graphics
stats
survival ≥ 2.38
ggplot2
MASS
flexsurv
Rcpp

LinkingTo

Rcpp
RcppArmadillo