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>.
|Author||Gabriela Cybis [aut, cre], Marcio Valk [aut], Kazuki Yokoyama [ctb]|
|Maintainer||Gabriela Cybis <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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