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 SÃlvia RC Lopes (2018)
Clustering and classification inference for high dimension low sample size 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.