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• W2079400333 abstract "In this paper, we construct a family of nonparametric multivariate multisample tests based on depth rankings. These tests are of Kruskal-Wallis type in the sense that the samples are variously ordered. However, unlike the Kruskal-Wallis test, these tests are based upon a depth ranking using a statistical depth function such as the halfspace depth or the Mahalanobis depth, etc. The types of tests we propose are adapted to the depth function that is most appropriate for the application. Under the null hypothesis that all samples come from the same distribution, we show that the test statistic asymptotically has a chi-square distribution. Some comparisons of power are made with the Hotelling T2, and the test of Choi and Marden (1997). Our test is particularly recommended when the data are of unknown distribution type where there is some evidence that the density contours are not elliptical. However, when the data are normally distributed, we often obtain high relative power." @default.
• W2079400333 created "2016-06-24" @default.
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• W2079400333 date "2012-01-01" @default.
• W2079400333 modified "2023-10-06" @default.
• W2079400333 title "A nonparametric multivariate multisample test based on data depth" @default.
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• W2079400333 doi "https://doi.org/10.1214/12-ejs692" @default.
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