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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 |
| Reference manual: | uni.survival.tree.pdf |
| 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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