Poisson随机测度与超临界多类型Markov分支过程

Pub Date : 2022-01-21 DOI:10.1080/15326349.2021.2016446
M. Slavtchova-Bojkova, O. Hyrien, N. Yanev
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引用次数: 1

摘要

摘要我们考虑了在泊松随机测度生成的时间点上发生迁移的多类型马尔可夫分支过程。这些模型可应用于研究多类型细胞群体的进化,其中新细胞根据时变迁移机制加入群体。本文的重点是超临界情况。我们研究了不同泊松随机测度率下过程的极限行为。特别地,我们证明了一个类似于强LLN的结果,并建立了极限正态分布。
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Poisson random measures and supercritical multitype Markov branching processes
Abstract We consider multitype Markov branching processes with immigration occurring at time points generated by Poisson random measures. These models find applications to study evolution of multitype cell populations in which new cells join the population according to a time-varying immigration mechanism. The focus of this paper is the supercritical case. We investigate the limiting behavior of the process for different rates of the Poisson random measures. In particular, we prove a result analogous to a strong LLN and establish limiting normal distributions.
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