Large deviation principle for additive functionals of semi-Markov processes

被引：0

作者：

Oprisan, Adina ^{[1
]}

机构：

[1] New Mexico State Univ, Dept Math Sci, Las Cruces, NM 88003 USA

来源：

STOCHASTIC ANALYSIS AND APPLICATIONS | 2023年 / 41卷 / 02期

关键词：

Semi-Markov processes; renewal processes; almost sure functional central limit theorem; large deviations; martingale decomposition; CENTRAL-LIMIT-THEOREM;

D O I：

10.1080/07362994.2021.2007777

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

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 D[0, infinity). A martingale decomposition for additive functionals of Markov renewal processes is employed.

引用

页码：257 / 275

页数：19

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