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  • 标题:A New Nonparametric Test for Two Sample Multivariate Location Problem with Application to Astronomy
  • 本地全文:下载
  • 作者:Soumita Modak ; Uttam Bandyopadhyay
  • 期刊名称:Journal of Statistical Theory and Applications (JSTA)
  • 电子版ISSN:1538-7887
  • 出版年度:2019
  • 卷号:18
  • 期号:2
  • 页码:136-146
  • DOI:10.2991/jsta.d.190515.002
  • 语种:English
  • 出版社:Atlantis Press
  • 摘要:This paper provides a nonparametric test for the identity of two multivariate continuous distribution functions when they differ in locations. The test uses Wilcoxon rank-sum statistics on distances between observations for each of the components and is unaffected by outliers. It is numerically compared with two existing procedures in terms of power. The simulation study shows that its power is strictly increasing in the sample sizes and/or in the number of components. The applicability of this test is demonstrated by use of two astronomical data sets on early-type galaxies.
  • 关键词:Nonparametric multivariate test; combination of Wilcoxon; rank-sum tests; outliers; large sample distribution; astronomical data; compatibility test
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