对于f-ergodic马尔科夫过程的子指数下限
Miha Brešar1, Aleksandar Mijatović1
1Department of Statistics, University of Warwick, Coventry, UK.
概括
研究人员开发了一种新的标准,以确定马尔科夫过程收率的下限. 这种方法使用了新的马丁加尔条件和路径智能参数来分析不变的测量尾巴和收速度.
科学领域:
- 可能性理论概率理论.
- 随机过程 随机过程
- 埃尔戈迪克理论 埃尔戈迪克理论
背景情况:
- 马尔科夫过程是建模动态系统的基础.
- 了解对不变指标的收率对于分析系统长期行为至关重要.
- 现有的方法主要集中在上限,使得下限的探索较少.
研究的目的:
- 引入一个新的标准,以确定连续时间 ergodic 马尔科夫过程 f-变异的收率的下限.
- 开发一种通用方法来证明不变测量尾和收率的下限.
- 为上限提供类似于利亚普诺夫漂移条件的方法.
主要方法:
- 针对特定的马尔科夫过程函数的超级和亚马丁盖尔条件的开发.
- 使用路径参数从有界集合中推导出出行程高度和持续时间的下界.
- 将标准应用于圆扩散和莱维驱动的随机微分方程.
主要成果:
- 建立了一个新的标准,用于f-变化中的收率的下限.
- 该方法成功地推导出了不变量尾的下限.
- 应用于特定的模型,导出的下限与已知的上限异常匹配,证实了收率.
结论:
- 开发的标准提供了一个一般的方法来证明马尔科夫过程收的下界.
- 使用路径智能参数和马丁盖尔条件的方法广泛适用.
- 这项工作补充了分析收率的现有方法,预计将得到广泛应用.
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