Tests for the multivariate -sample problem based on the empirical characteristic function

Marie Hušková and Simos Meintanis

Journal of Nonparametric Statistics, 2008, vol. 20, issue 3, 263-277

Abstract: Tests for the multivariate k-sample problem are considered. The tests are based on the weighted L2 distance between empirical characteristic functions, and afford an interesting interpretation in terms of a corresponding test statistic based on the L2 distance of pairs of non-parametric density estimators. Depending on the choice of weighting, a corresponding Dirac-type weight function reduces the test to a normalised version of the L2 distance between the sample means of the k populations. Theoretical and computational issues are considered, while the finite-sample implementation based on the permutation distribution of the test statistic shows that the new test performs well in comparison with alternative procedures of the change-point type.

Date: 2008
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Citations: View citations in EconPapers (16)

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DOI: 10.1080/10485250801948294

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