Large deviations for empirical measures of mean-field Gibbs measures

被引:14
|
作者
Liu, Wei [1 ,2 ]
Wu, Liming [3 ]
机构
[1] Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Computat Sci Hubei Key Lab, Wuhan 430072, Hubei, Peoples R China
[3] Univ Clermont Auvergne, Lab Math Blaise Pascal, CNRS UMR 6620, 3 Pl Vasarely, F-63178 Aubiere, France
关键词
Large deviations; Empirical measure; U-statistics; Interacting particle systems; McKean-Vlasov equation; Mean-field Gibbs measure; PRINCIPLE;
D O I
10.1016/j.spa.2019.01.008
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper, we show that the empirical measure of mean-field model satisfies the large deviation principle with respect to the weak convergence topology or the stronger Wasserstein metric, under the strong exponential integrability condition on the negative part of the interaction potentials. In contrast to the known results we prove this without any continuity or boundedness condition on the interaction potentials. The proof relies mainly on the law of large numbers and the exponential decoupling inequality of de la Pena for U-statistics. (C) 2019 Elsevier B.V. All rights reserved.
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页码:503 / 520
页数:18
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