A distance based two-sample test of means difference for multivariate datasets

Alexander Novoselsky, Eugene Kagan

Research output: Contribution to journalArticlepeer-review

Abstract

In the paper we present a new test for comparison of the means of multivariate samples with unknown distributions. The test is based on the comparison of the distributions of the distances between the samples’ elements and their means using univariate two-sample Kolmogorov–Smirnov test. The activity of the suggested method is illustrated by numerical analysis of the real-world and simulated data.

Original languageEnglish
Pages (from-to)4861-4874
Number of pages14
JournalStatistical Papers
Volume65
Issue number8
DOIs
StatePublished - Oct 2024

Keywords

  • 62H15—Hypothesis testing in multivariate analysis
  • Distance-based statistic
  • Multivariate means test
  • Multivariate two sample problem
  • Two-sample Kolmogorov–Smirnov test

Fingerprint

Dive into the research topics of 'A distance based two-sample test of means difference for multivariate datasets'. Together they form a unique fingerprint.

Cite this