uclust: Clustering and Classification Inference with U-Statistics

Clustering and classification inference for high dimension low sample size (HDLSS) data with U-statistics. The package contains implementations of nonparametric statistical tests for sample homogeneity, group separation, clustering, and classification of multivariate data. The methods have high statistical power and are tailored for data in which the dimension L is much larger than sample size n. See Gabriela B. Cybis, Marcio Valk and Sílvia RC Lopes (2018) <doi:10.1080/00949655.2017.1374387> and Marcio Valk and Gabriela B. Cybis (2018) <arXiv:1805.12179>.

Version: 0.1.0
Depends: R (≥ 3.4.0), dendextend, robcor
Suggests: testthat
Published: 2019-02-11
Author: Gabriela Cybis [aut, cre], Marcio Valk [aut], Kazuki Yokoyama [ctb]
Maintainer: Gabriela Cybis <gcybis at gmail.com>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: uclust results


Reference manual: uclust.pdf
Package source: uclust_0.1.0.tar.gz
Windows binaries: r-devel: uclust_0.1.0.zip, r-release: uclust_0.1.0.zip, r-oldrel: uclust_0.1.0.zip
OS X binaries: r-release: uclust_0.1.0.tgz, r-oldrel: uclust_0.1.0.tgz


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