一维随机走路的完整记录统计数据
Léo Régnier1, Maxim Dolgushev1, Olivier Bénichou1
1<a href="https://ror.org/04zaaa143">Laboratoire de Physique Théorique de la Matière Condensée</a>, CNRS, Sorbonne University, 4 Place Jussieu, 75005 Paris, France.
Physical review. E
|July 18, 2024
概括
本研究引入了一个新的框架来分析记录统计数据和随机过程中的动态. 它为关键可观测值提供了一般表达式,增强了对随机现象的理解.
科学领域:
- 统计物理 统计物理
- 随机过程 随机过程
- 可能性理论概率理论.
背景情况:
- 记录动态对于分析顺序数据和随机过程至关重要.
- 现有的方法往往缺乏统一的框架来进行全面的统计分析.
- 了解记录统计对于各种领域至关重要,从金融到物理学.
研究的目的:
- 为完整的记录统计制定一个全面的分析框架.
- 导出与记录动态相关的可观察值的一般表达式.
- 将形式主义应用于各种复杂的随机过程.
主要方法:
- 多次时间分布形式主义的发展.
- 条件可观测的一般表达式的导出.
- 适用于有偏见的随机走路,运行和动态以及随机重置.
主要成果:
- 一个统一的框架来分析记录数量,实现时间和记录间隔.
- 对于有条件的记录数和到达记录的有条件时间的一般表达式.
- 在各种随机模型中展示框架的适用性.
结论:
- 开发的框架为研究随机过程中的记录动态提供了一个强大的工具.
- 提供了对连续随机事件的统计性质的更深入的见解.
- 适用于广泛的物理和数学系统,表现出破纪录的行为.
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