Asymptotic normality of a consistent estimator of maximum mean discrepancy in Hilbert space

Natsumi Makigusa and Kanta Naito

Statistics & Probability Letters, 2020, vol. 156, issue C

Abstract: This paper is concerned with a consistent estimator of the maximum mean discrepancy in the Hilbert space, which is always asymptotically normally distributed. The proposed estimator is constructed by modifying the naive estimator of the maximum mean discrepancy appropriately.

Keywords: Asymptotic normality; Hilbert space; Kernel method; Maximum mean discrepancy (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.spl.2019.108596

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