一种分区方法,用于界定通用反应网络的连续时间马尔科夫链模型
Guillaume Ballif1, Laurent Pfeiffer2, Jakob Ruess1
1Inria Saclay, Palaiseau, 91120, France.
Mathematical biosciences
|February 6, 2026
概括
我们开发了一种方法,通过创建更简单的边界过程来分析反应网络中的复杂马尔科夫链. 这种方法有助于确定系统属性,如静态分布和数值准确性.
科学领域:
- 随机模型的建模
- 化学动力学 化学动力学
- 计算生物学是一种计算生物学.
背景情况:
- 随机反应网络通常由多维连续时间马尔科夫链建模.
- 分析这些复杂的系统,特别是它们在无限和数值近似的行为,是具有挑战性的.
研究的目的:
- 介绍一种用于确定多维连续时间马尔科夫链的属性的一般方法.
- 开发复杂的马尔科夫链的分析和数值可处理的界限过程.
- 为构建最佳界限过程得出明确的公式.
主要方法:
- 国家空间的分区.
- 构建一维的出生和死亡过程.
- 合论证和运输理论的合论证
- 对静态分布和切断误差的分析.
主要成果:
- 开发了一种方法来构建一维的出生和死亡过程,这些过程绑定了原来的多维马尔科夫链.
- 为最佳的边界过程构建衍生了明确的公式.
- 证明了该方法在分析静态分布和状态空间截断错误方面的实用性.
- 用两个化学反应网络示例说明了方法.
结论:
- 拟议的方法提供了一种通用和实用的方法,用于分析随机反应网络中的复杂马尔科夫链.
- 边界过程简化了系统属性的分析,包括长期行为和数值准确性.
- 选择状态空间分区对于获得相关和准确的结果至关重要.
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