On the averaging principle for stochastic differential equations driven by G-Levy process

被引：0

作者：

Yuan, Mingxia ^{[1
]}

Wang, Bingjun ^{[2
]}

Yang, Zhiyan ^{[3
]}

机构：

[1] Nanjing Vocat Inst Transport Technol, Nanjing 211188, Peoples R China

[2] Jinling Inst Technol, Nanjing 211169, Peoples R China

[3] Nanjing Inst Technol, Nanjing 211167, Peoples R China

来源：

STATISTICS & PROBABILITY LETTERS | 2023年 / 195卷

基金：

中国国家自然科学基金;

关键词：

G-L?vy process; Averaging principle; Non-Lipschitz; Stochastic differential equation; STRONG-CONVERGENCE; SYSTEMS;

D O I：

10.1016/j.spl.2023.109789

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 investigate the averaging principle for stochastic differential equation driven by G-Levy process. By the BDG inequality for G-stochastic calculus with respect to G-Levy process, we show that the solution of averaged stochastic differential equation driven by G-Levy process converges to that of the standard one, under non-Lipschitz condition, in the mean square sense and also in capacity. An example is presented to illustrate the efficiency of the obtained results.(c) 2023 Elsevier B.V. All rights reserved.

引用

页数：8

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