Test for diagonal symmetry in high dimension
Yongli Sang
Statistics & Probability Letters, 2024, vol. 205, issue C
Abstract:
Utilizing the energy distance and energy statistics, Sang and Dang (2020) proposed a test statistic as a difference of two U-statistics for the diagonal symmetry test of a p-vector X. Under the regular setting where the dimensionality of the random vector is fixed, the test statistic is a degenerate U-statistic and hence converges to a mixture of chi-squared distributions. In this paper, we test the diagonal symmetry of X in a more realistic setting where both the sample size and the dimensionality are diverging to infinity. Our theoretical results reveal that the degenerate U-statistic admits a central limit theorem in the high dimensional setting and the accuracy of normal approximation can increase with dimensionality. We then construct a powerful and consistent test for the diagonal symmetry problem based on the asymptotic normality. Simulation studies are conducted to illustrate the performances of the test.
Keywords: Asymptotic normality; Energy distance; High-dimensional diagonal symmetry; U-statistic (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:205:y:2024:i:c:s0167715223001840
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DOI: 10.1016/j.spl.2023.109960
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