2015
DOI: 10.1093/biomet/asu072
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A Wilcoxon-Mann-Whitney-type test for infinite-dimensional data

Abstract: The Wilcoxon-Mann-Whitney test is a robust competitor of the t-test in the univariate setting. For finite dimensional multivariate data, several extensions of the Wilcoxon-Mann-Whitney test have been shown to have better performance than Hotelling's T 2 test for many non-Gaussian distributions of the data. In this paper, we study a Wilcoxon-Mann-Whitney type test based on spatial ranks for data in infinite dimensional spaces. We demonstrate the performance of this test using some real and simulated datasets. W… Show more

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Cited by 28 publications
(18 citation statements)
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References 32 publications
(46 reference statements)
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“…The HDI and GI values were compared between the municipalities with and without CAs using the non-parametric Wilcoxon-Mann-Whitney test (CHAKRABORTY; CHAUDHURI, 2015;FAY;PROSCHAN, 2010). The municipalities with and without sustainable use CAs and those with and without full protection CAs were also compared separately.…”
Section: Methodsmentioning
confidence: 99%
“…The HDI and GI values were compared between the municipalities with and without CAs using the non-parametric Wilcoxon-Mann-Whitney test (CHAKRABORTY; CHAUDHURI, 2015;FAY;PROSCHAN, 2010). The municipalities with and without sustainable use CAs and those with and without full protection CAs were also compared separately.…”
Section: Methodsmentioning
confidence: 99%
“…Further, it is shown in Oja (2010, pp. Recently, a two sample Wilcoxon-Mann-Whitney type test based on spatial ranks in infinite dimensional spaces has been studied by Chakraborty and Chaudhuri (2015). In any separable Banach space, the asymptotic distributions of T SR and Q T SR are the same.…”
Section: Definition 201mentioning
confidence: 99%
“…(2) 0 for large values of ||T SR ||. Recently, a two sample Wilcoxon-Mann-Whitney type test based on spatial ranks in infinite dimensional spaces have been studied by Chakraborty and Chaudhuri (2014). Note that if X = R, S x = sign(x).…”
Section: We Reject Hmentioning
confidence: 99%