状态切换过程转移速率矩阵摄动下的比较定理与稳定性

IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Jinghai Shao
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引用次数: 0

摘要

摘要建立了状态依赖状态切换扩散过程的比较定理,使我们能够简单地用马尔可夫链对状态依赖状态切换扩散过程的演化进行路径控制。此外,给出了跃迁率矩阵摄动下马尔可夫状态切换过程稳定性的一个尖锐估计。我们的方法基于基于Skorokhod表示定理精神的转换过程的详细构造,该定理根据所处理的问题而变化。特别是,该方法可以处理无限状态空间中的切换过程,而不一定是生-死类型。作为一个应用,一些已知的关于状态相关状态切换过程的遍历性和稳定性的结果可以得到改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison theorem and stability under perturbation of transition rate matrices for regime-switching processes
Abstract A comparison theorem for state-dependent regime-switching diffusion processes is established, which enables us to pathwise-control the evolution of the state-dependent switching component simply by Markov chains. Moreover, a sharp estimate on the stability of Markovian regime-switching processes under the perturbation of transition rate matrices is provided. Our approach is based on elaborate constructions of switching processes in the spirit of Skorokhod’s representation theorem varying according to the problem being dealt with. In particular, this method can cope with switching processes in an infinite state space and not necessarily of birth–death type. As an application, some known results on the ergodicity and stability of state-dependent regime-switching processes can be improved.
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来源期刊
Journal of Applied Probability
Journal of Applied Probability 数学-统计学与概率论
CiteScore
1.50
自引率
10.00%
发文量
92
审稿时长
6-12 weeks
期刊介绍: Journal of Applied Probability is the oldest journal devoted to the publication of research in the field of applied probability. It is an international journal published by the Applied Probability Trust, and it serves as a companion publication to the Advances in Applied Probability. Its wide audience includes leading researchers across the entire spectrum of applied probability, including biosciences applications, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used. A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.
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