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CLT for approximating ergodic limit of SPDEs via a full discretization

文献类型：期刊论文

作者Chen, Chuchu; Dang, Tonghe1; Hong, Jialin; Zhou, Tau
刊名STOCHASTIC PROCESSES AND THEIR APPLICATIONS
出版日期2023-03-01
卷号157页码:1-41
关键词Central limit theorem Stochastic partial differential equation Full discretization Poisson equation Ergodic limit
ISSN号0304-4149
DOI10.1016/j.spa.2022.11.015
英文摘要In order to characterize quantitatively the fluctuations between the ergodic limit and the time -averaging estimator, we establish a central limit theorem for a full discretization of the parabolic SPDE, which shows that the normalized time-averaging estimator converges weakly to a normal distribution as the time stepsize tends to 0. A key ingredient in the proof is to extract an appropriate martingale difference series sum from the normalized time-averaging estimator via the Poisson equation, so that convergences of such a sum and the remainder are well balanced.(c) 2022 Elsevier B.V. All rights reserved.
资助项目National key R&D Program of China ; National Natural Science Foundation of China ; Youth Innovation Promotion Association CAS, China ; [2020YFA0713701] ; [11971470] ; [11871068] ; [12031020] ; [12022118]
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000899376200001
出版者ELSEVIER
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/60512]  
专题中国科学院数学与系统科学研究院
通讯作者Dang, Tonghe
作者单位1.Chinese Acad Sci, ICMSEC, LSEC, Acad Math & Syst Sci, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Chuchu,Dang, Tonghe,Hong, Jialin,et al. CLT for approximating ergodic limit of SPDEs via a full discretization[J]. STOCHASTIC PROCESSES AND THEIR APPLICATIONS,2023,157:1-41.
APA Chen, Chuchu,Dang, Tonghe,Hong, Jialin,&Zhou, Tau.(2023).CLT for approximating ergodic limit of SPDEs via a full discretization.STOCHASTIC PROCESSES AND THEIR APPLICATIONS,157,1-41.
MLA Chen, Chuchu,et al."CLT for approximating ergodic limit of SPDEs via a full discretization".STOCHASTIC PROCESSES AND THEIR APPLICATIONS 157(2023):1-41.

入库方式： OAI收割

来源：数学与系统科学研究院

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