两个不同单变量分布间Wasserstein型距离的中心极限定理

IF 1.2 2区数学 Q2 STATISTICS & PROBABILITY

Annales De L Institut Henri Poincare-probabilites Et Statistiques Pub Date : 2020-05-01 DOI:10.1214/19-aihp990

Philippe Berthet, J. Fort, T. Klein

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引用次数: 2

摘要

本文研究了r上两个不同连续分布F和G之间的Wasserstein型代价的自然非参数估计量，该估计量基于边际为F, G和任意联合分布的样本的阶统计量。在一般条件下证明了尾部与代价函数的中心极限定理。特别是，p>1阶的Wasserstein距离和兼容的经典概率分布满足这些条件。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Central Limit Theorem for Wasserstein type distances between two distinct univariate distributions

In this article we study the natural nonparametric estimator of a Wasserstein type cost between two distinct continuous distributions F and G on R. The estimator is based on the order statistics of a sample having marginals F, G and any joint distribution. We prove a central limit theorem under general conditions relating the tails and the cost function. In particular, these conditions are satisfied by Wasserstein distances of order p>1and compatible classical probability distributions.

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来源期刊

Annales De L Institut Henri Poincare-probabilites Et Statistiques 数学-统计学与概率论

CiteScore

2.70

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The Probability and Statistics section of the Annales de l’Institut Henri Poincaré is an international journal which publishes high quality research papers. The journal deals with all aspects of modern probability theory and mathematical statistics, as well as with their applications.