Hoeffding–Serfling Inequality for U-Statistics Without Replacement

Jianhang Ai (), Ondřej Kuželka () and Yuyi Wang ()
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Jianhang Ai: Czech Technical University in Prague
Ondřej Kuželka: Czech Technical University in Prague
Yuyi Wang: ETH Zurich

Journal of Theoretical Probability, 2023, vol. 36, issue 1, 390-408

Abstract: Abstract Concentration inequalities quantify random fluctuations of functions of random variables, typically by bounding the probability that such a function differs from its expected value by more than a certain amount. In this paper we study one particular concentration inequality, the Hoeffding–Serfling inequality for U-statistics of random variables sampled without replacement from a finite set and extend recent results of Bardenet and Maillard (Bernoulli 21(3):1361–1385, 2015) to cover the U-statistics setting.

Keywords: Hoeffding–Serfling inequality; U-statistics; Sampling without replacement; 60F10 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10959-022-01169-x

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