Crandore Hub

uni.survival.tree

A Survival Tree Based on Stabilized Score Tests for High-dimensional Covariates

A classification (decision) tree is constructed from survival data with high-dimensional covariates. The method is a robust version of the logrank tree, where the variance is stabilized. The main function "uni.tree" returns a classification tree for a given survival dataset. The inner nodes (splitting criterion) are selected by minimizing the P-value of the two-sample the score tests. The decision of declaring terminal nodes (stopping criterion) is the P-value threshold given by an argument (specified by user). This tree construction algorithm is proposed by Emura et al. (2021, in review).

Versions across snapshots

VersionRepositoryFileSize
1.5 rolling linux/jammy R-4.5 uni.survival.tree_1.5.tar.gz 40.5 KiB
1.5 rolling linux/noble R-4.5 uni.survival.tree_1.5.tar.gz 40.5 KiB
1.5 rolling source/ R- uni.survival.tree_1.5.tar.gz 7.5 KiB
1.5 latest linux/jammy R-4.5 uni.survival.tree_1.5.tar.gz 40.5 KiB
1.5 latest linux/noble R-4.5 uni.survival.tree_1.5.tar.gz 40.5 KiB
1.5 latest source/ R- uni.survival.tree_1.5.tar.gz 7.5 KiB
1.5 2026-04-26 source/ R- uni.survival.tree_1.5.tar.gz 7.5 KiB
1.5 2026-04-23 source/ R- uni.survival.tree_1.5.tar.gz 7.5 KiB
1.5 2026-04-09 windows/windows R-4.5 uni.survival.tree_1.5.zip 43.8 KiB
1.5 2025-04-20 source/ R- uni.survival.tree_1.5.tar.gz 7.5 KiB

Dependencies (latest)

Depends