Interpoint distance-based two-sample tests for functional data

Hikaru Yamaguchi and Hidetoshi Murakami

Communications in Statistics - Theory and Methods, 2024, vol. 53, issue 8, 2771-2791

Abstract: This study examines interpoint distance-based tests for random elements from probability distributions in infinite-dimensional space. Some asymptotic properties such as the limiting distributions and the asymptotic power of the Biswas–Ghosh type test (Biswas and Ghosh in J Multivar Anal 123: 160–171, 2014) are presented using the theory of U-statistic. In addition, the p-value approximation based on the jackknife variance estimators and the Welch–Satterthwaite equation is proposed. Simulation studies are conducted to evaluate the performance of the proposed test statistics in functional data analysis. The proposed tests are shown to have better power than the existing method for functional data in some situations.

Date: 2024
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DOI: 10.1080/03610926.2022.2148475

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