A classification (decision) tree is constructed from survival data with highdimensional 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 Pvalue of the twosample the score tests. The decision of declaring terminal nodes (stopping criterion) is the Pvalue threshold given by an argument (specified by user). This tree construction algorithm is proposed by Emura et al. (2021, in review).
Package details 


Author  Takeshi Emura and WeiChern Hsu 
Maintainer  Takeshi Emura <takeshiemura@gmail.com> 
License  GPL3 
Version  1.5 
Package repository  View on CRAN 
Installation 
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