Journal
JOURNAL OF MULTIVARIATE ANALYSIS
Volume 88, Issue 1, Pages 190-206Publisher
ELSEVIER INC
DOI: 10.1016/S0047-259X(03)00079-4
Keywords
multivariate two-sample test; bootstrapping; projection method; orthogonal invariance; Cramer test
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In this paper we propose a new test for the multivariate two-sample problem. The test statistic is the difference of the sum of all the Euclidean interpoint distances between the random variables from the two different samples and one-half of the two corresponding sums of distances of the variables within the same sample. The asymptotic null distribution of the test statistic is derived using the projection method and shown to be the limit of the bootstrap distribution. A simulation study includes the comparison of univariate and multivariate normal distributions for location and dispersion alternatives. For normal location alternatives the new test is shown to have power similar to that of the t- and T-2-Test. (C) 2003 Elsevier Inc. All rights reserved.
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