马氏分支—移民系统的自正则大偏差

Self-Normalized Large Deviations for Markov Branching-Immigration Systems

  • 摘要: 该论文研究了上临界连续时间马尔可夫分支过程Z(t),t ≥ 0的自正则大偏差.具体而言,我们的研究聚焦于连续时间情形并推广了Athreya1的结论.此外,我们还探讨了具有移民的分支过程的自正则大偏差.在分析中,我们利用了Shao2提出的独立同分布随机变量的自正则大偏差结果.

     

    Abstract: The paper investigates the self-normalized large deviations for the supercritical continuous-time Markov branching process Z(t), t ≥ 0. Specifically, our study focuses on the continuous-time case and extends the conclusions drawn by Athreya1. Additionally, we explore the self-normalized large deviation in the context of branching processes with immigration. In our analysis, we utilize the results of self-normalized large deviations for i.i.d. random variables presented in Shao2.

     

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