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arXiv 1403.0201stat.ME
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无穷维数据的Wilcoxon-Mann-Whitney型检验

A Wilcoxon-Mann-Whitney type test for infinite dimensional data

Anirvan Chakraborty, Probal Chaudhuri

摘要:

Wilcoxon-Mann-Whitney检验是单变量设置中t检验的稳健竞争者。对于有限维多变量数据,Wilcoxon-Mann-Whitney检验的几个扩展已被证明对许多非高斯分布的数据具有比Hotelling的$T^{2}$检验更好的性能。本文研究了无限维空间中基于空间秩的Wilcoxon-Mann-Whitney类型检验。我们使用一些真实的和模拟的数据集证明了这个测试的性能。我们还研究了所提出的测试的渐近性质,并比较了广泛的竞争测试的测试。

英文摘要:

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. We also investigate the asymptotic properties of the proposed test and compare the test with a wide range of competing tests.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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