Open AccessNonparametric Tests Applicable to High Dimensional Data
Author(s) -
František Rublík
Publication year - 2019
Publication title -
österreichische zeitschrift für statistik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.342
H-Index - 9
ISSN - 1026-597X
DOI - 10.17713/ajs.v48i4.654
Subject(s) - nonparametric statistics , multivariate statistics , dimension (graph theory) , statistics , set (abstract data type) , mathematics , sample (material) , data set , data mining , sample size determination , computer science , algorithm , combinatorics , chemistry , chromatography , programming language
Constructions of data driven ordering of set of multivariate observations are presented. The methods employ also dissimilarity measures. The ranks are used in the construction of test statistics for location problem and in the construction of the corresponding multiple comparisons rule. An important aspect of the resulting procedures is that they can be used also in the multisample setting and in situations where the sample size is smaller than the dimension of the observations. The performance of the proposed procedures is illustrated by simulations.