HTT: Hypothesis Testing Tree

A novel decision tree algorithm in the hypothesis testing framework. The algorithm examines the distribution difference between two child nodes over all possible binary partitions. The test statistic of the hypothesis testing is equivalent to the generalized energy distance, which enables the algorithm to be more powerful in detecting the complex structure, not only the mean difference. It is applicable for numeric, nominal, ordinal explanatory variables and the response in general metric space of strong negative type. The algorithm has superior performance compared to other tree models in type I error, power, prediction accuracy, and complexity.

Version: 0.1.2
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.6), ggraph, igraph, ggplot2
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, MASS
Published: 2023-03-12
Author: Jiaqi Hu [cre, aut], Zhe Gao [aut], Bo Zhang [aut], Xueqin Wang [aut]
Maintainer: Jiaqi Hu <hujiaqi at mail.ustc.edu.cn>
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: HTT results

Documentation:

Reference manual: HTT.pdf
Vignettes: HTT: Hypothesis Testing Tree

Downloads:

Package source: HTT_0.1.2.tar.gz
Windows binaries: r-devel: HTT_0.1.2.zip, r-release: HTT_0.1.2.zip, r-oldrel: HTT_0.1.2.zip
macOS binaries: r-release (arm64): HTT_0.1.2.tgz, r-oldrel (arm64): HTT_0.1.2.tgz, r-release (x86_64): HTT_0.1.2.tgz
Old sources: HTT archive

Linking:

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