Asymptotic normality of a generalized maximum mean discrepancy estimator

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 both under equality these distributions and alternative hypothesis, so allowing to achieve k-sample test distributions. A simulation study that allows compare proposed existing ones provided.