{ "_id": "6a1e87851d7bb097a0a679fe", "Package": "uni.survival.tree", "Type": "Package", "Title": "A Survival Tree Based on Stabilized Score Tests for\nHigh-dimensional Covariates", "Version": "1.5", "Author": "Takeshi Emura and Wei-Chern Hsu", "Maintainer": "Takeshi Emura ", "Description": "A classification (decision) tree is constructed from\nsurvival data with high-dimensional covariates. The method is a\nrobust version of the logrank tree, where the variance is\nstabilized. The main function \"uni.tree\" returns a\nclassification tree for a given survival dataset. The inner\nnodes (splitting criterion) are selected by minimizing the\nP-value of the two-sample the score tests. The decision of\ndeclaring terminal nodes (stopping criterion) is the P-value\nthreshold given by an argument (specified by user). This tree\nconstruction algorithm is proposed by Emura et al. 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