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Asymptotic normality of a generalized maximum mean discrepancy estimator

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  • Balogoun, Armando Sosthène Kali
  • Nkiet, Guy Martial
  • Ogouyandjou, Carlos

Abstract

In this paper, we propose an estimator of the generalized maximum mean discrepancy between several probability distributions, constructed by modifying a naive estimator. Asymptotic normality is obtained for this estimator both under equality of these distributions and under the alternative hypothesis, so allowing to achieve a k-sample test for equality of distributions. A simulation study that allows to compare the proposed test to existing ones is provided.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:stapro:v:169:y:2021:i:c:s0167715220302649
    DOI: 10.1016/j.spl.2020.108961
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    Cited by:

    1. Yongli Sang & Xin Dang, 2024. "Asymptotic normality of a modified estimator of Gini distance correlation," Statistical Papers, Springer, vol. 65(8), pages 4843-4860, October.

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