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).

Version:	1.5
Depends:	survival, compound.Cox
Published:	2021-03-22
Author:	Takeshi Emura and Wei-Chern Hsu
Maintainer:	Takeshi Emura <takeshiemura at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	uni.survival.tree results

Documentation:

Reference manual:

uni.survival.tree.pdf

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Package source:	uni.survival.tree_1.5.tar.gz
Windows binaries:	r-devel: uni.survival.tree_1.5.zip, r-release: uni.survival.tree_1.5.zip, r-oldrel: uni.survival.tree_1.5.zip
macOS binaries:	r-release (arm64): uni.survival.tree_1.5.tgz, r-oldrel (arm64): uni.survival.tree_1.5.tgz, r-release (x86_64): uni.survival.tree_1.5.tgz, r-oldrel (x86_64): uni.survival.tree_1.5.tgz
Old sources:	uni.survival.tree archive

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