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.
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页数：8
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