Clustering and classification inference for high dimension low sample size (HDLSS) data with Ustatistics. 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>, Marcio Valk and Gabriela B. Cybis (2020) <doi:10.1080/10618600.2020.1796398>, Debora Z. Bello, Marcio Valk and Gabriela B. Cybis (2021) <arXiv:2106.09115>.
Package details 


Author  Gabriela Cybis [aut, cre], Marcio Valk [aut], Kazuki Yokoyama [ctb], Debora Zava Bello [ctb] 
Maintainer  Gabriela Cybis <gcybis@gmail.com> 
License  GPL3 
Version  1.0.0 
Package repository  View on CRAN 
Installation 
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