Large deviation principle for additive functionals of semi-Markov processes

IF 0.8 4区数学 Q3 MATHEMATICS, APPLIED

Stochastic Analysis and Applications Pub Date : 2021-12-09 DOI:10.1080/07362994.2021.2007777

Adina Oprisan

引用次数: 0

Abstract

Abstract A large deviation principle (LDP) for a class of additive functionals of semi-Markov processes and their associated Markov renewal processes is studied via an almost sure functional central limit theorem. The rate function corresponding to the deviations from the paths of the corresponding empirical processes with logarithmic averaging is determined as a relative entropy with respect to the Wiener measure on A martingale decomposition for additive functionals of Markov renewal processes is employed.

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半马尔可夫过程加性泛函的大偏差原理

摘要利用几乎确定泛函中心极限定理，研究了一类半马尔可夫过程及其相关马尔可夫更新过程的加性泛函的大偏差原理。对于马尔可夫更新过程的加性泛函的鞅分解，采用对数平均法确定了与相应经验过程的路径偏差相对应的速率函数，作为相对熵。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Stochastic Analysis and Applications 数学-统计学与概率论

CiteScore

2.70

自引率

7.70%

发文量

审稿时长

6-12 weeks

期刊介绍： Stochastic Analysis and Applications presents the latest innovations in the field of stochastic theory and its practical applications, as well as the full range of related approaches to analyzing systems under random excitation. In addition, it is the only publication that offers the broad, detailed coverage necessary for the interfield and intrafield fertilization of new concepts and ideas, providing the scientific community with a unique and highly useful service.