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

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  • Makigusa, Natsumi
  • Naito, Kanta

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.

Suggested Citation

  • Makigusa, Natsumi & Naito, Kanta, 2020. "Asymptotic normality of a consistent estimator of maximum mean discrepancy in Hilbert space," Statistics & Probability Letters, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:stapro:v:156:y:2020:i:c:s0167715219302421
    DOI: 10.1016/j.spl.2019.108596
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    Cited by:

    1. Balogoun, Armando Sosthène Kali & Nkiet, Guy Martial & Ogouyandjou, Carlos, 2021. "Asymptotic normality of a generalized maximum mean discrepancy estimator," Statistics & Probability Letters, Elsevier, vol. 169(C).
    2. Dawei Lu & Lina Wang, 2021. "On the Rates of Asymptotic Normality for Bernstein Polynomial Estimators in a Triangular Array," Methodology and Computing in Applied Probability, Springer, vol. 23(4), pages 1519-1536, December.

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