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Functional Large Deviations for Kac–Stroock Approximation to a Class of Gaussian Processes with Application to Small Noise Diffusions
Hui, Jiang1; Lihu, Xu2,3; Qingshan, Yang4
2024-11
Source PublicationJournal of Theoretical Probability
ISSN0894-9840
Volume37Pages:3015-3054
Abstract

In this paper, we establish the functional large deviation principle (LDP) for the Kac–Stroock approximations of a wild class of Gaussian processes constructed by telegraph types of integrals with L2-integrands under mild conditions and find the explicit form for their rate functions. Our investigation includes a broad range of kernels, such as those related to Brownian motions, fractional Brownian motions with whole Hurst parameters, and Ornstein–Uhlenbeck processes. Furthermore, we consider a class of non-Markovian stochastic differential equations driven by the Kac–Stroock approximation and establish their Freidlin–Wentzell type LDP. The rate function clearly indicates an interesting phase transition phenomenon as the approximating rate moves from one region to the other.

DOI10.1007/s10959-024-01354-0
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:001255155200001
PublisherSPRINGER/PLENUM PUBLISHER, S233 SPRING ST, NEW YORK, NY 10013
Scopus ID2-s2.0-85197195871
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF MATHEMATICS
Corresponding AuthorQingshan, Yang
Affiliation1.School of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing, China
2.Department of Mathematics, Faculty of Science and Technology, University of Macau, S.A.R., Macao
3.Zhuhai UM Science and Technology Research Institute, Zhuhai, China
4.KLAS, Key Laboratory of Big Data Analysis of Jilin Province, School of Mathematics and Statistics, Northeast Normal University, Changchun, China
Recommended Citation
GB/T 7714
Hui, Jiang,Lihu, Xu,Qingshan, Yang. Functional Large Deviations for Kac–Stroock Approximation to a Class of Gaussian Processes with Application to Small Noise Diffusions[J]. Journal of Theoretical Probability, 2024, 37, 3015-3054.
APA Hui, Jiang., Lihu, Xu., & Qingshan, Yang (2024). Functional Large Deviations for Kac–Stroock Approximation to a Class of Gaussian Processes with Application to Small Noise Diffusions. Journal of Theoretical Probability, 37, 3015-3054.
MLA Hui, Jiang,et al."Functional Large Deviations for Kac–Stroock Approximation to a Class of Gaussian Processes with Application to Small Noise Diffusions".Journal of Theoretical Probability 37(2024):3015-3054.
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