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arXiv 2005.05119math.PR
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超临界一般分支过程中Nerman鞅的高斯涨落和重对数律

Gaussian fluctuations and a law of the iterated logarithm for Nerman's martingale in the supercritical general branching process

Alexander Iksanov, Konrad Kolesko, Matthias Meiners

摘要:

在他的,到现在为止,经典的工作从1981年,奈尔曼广泛使用了一个关键的鞅$(W_t)_{t \geq 0}$证明依概率收敛,平均和几乎肯定,超临界一般分支过程(又名。Crump-Mode-Jagers分支过程)具有一般特征。鞅终值$W$的数字在他的结果的限制。我们研究的速度鞅,现在称为奈曼鞅,收敛到其极限$W$。更确切地说,假设存在的马尔萨斯参数$α> 0$和$W_0\in L^2$,我们证明了一个功能中心极限定理$(W-W_{t+s})_{s\in\mathbb{R}}$,适当规范化,作为$t\to\infty$。弱极限是随机标度的时变布朗运动。在一个附加的技术假设下,我们证明了$W-W_t$的重对数律。

英文摘要:

In his, by now, classical work from 1981, Nerman made extensive use of a crucial martingale $(W_t)_{t \geq 0}$ to prove convergence in probability, in mean and almost surely, of supercritical general branching processes (a.k.a. Crump-Mode-Jagers branching processes) counted with a general characteristic. The martingale terminal value $W$ figures in the limits of his results. We investigate the rate at which the martingale, now called Nerman's martingale, converges to its limit $W$. More precisely, assuming the existence of a Malthusian parameter $α> 0$ and $W_0\in L^2$, we prove a functional central limit theorem for $(W-W_{t+s})_{s\in\mathbb{R}}$, properly normalized, as $t\to\infty$. The weak limit is a randomly scaled time-changed Brownian motion. Under an additional technical assumption, we prove a law of the iterated logarithm for $W-W_t$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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