Asymptotic Gaussianity via coalescence probabilities in the Hammond-Sheffield urn

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY
Jan Lukas Igelbrink, A. Wakolbinger
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引用次数: 4

Abstract

For the renormalised sums of the random $\pm 1$-colouring of the connected components of $\mathbb Z$ generated by the coalescing renewal processes in the"power law P\'olya's urn"of Hammond and Sheffield we prove functional convergence towards fractional Brownian motion, closing a gap in the tightness argument of their paper. In addition, in the regime of the strong renewal theorem we gain insights into the coalescing renewal processes in the Hammond-Sheffield urn (such as the asymptotic depth of most recent common ancestors) and are able to control the coalescence probabilities of two, three and four individuals that are randomly sampled from $[n]$. This allows us to obtain a new, conceptual proof of the asymptotic Gaussianity (including the functional convergence) of the renormalised sums of more general colourings, which can be seen as an invariance principle beyond the main result of Hammond and Sheffield. In this proof, a key ingredient of independent interest is a sufficient criterion for the asymptotic Gaussianity of the renormalised sums in randomly coloured random partitions of $[n]$, based on Stein's method. Along the way we also prove a statement on the asymptotics of the coalescence probabilities in the long-range seedbank model of Blath, Gonz\'alez Casanova, Kurt, and Span\`o.
Hammond-Sheffield瓮中通过合并概率的渐近高斯性
renormalised金额的随机\点1美元边着色的连接组件\ mathbb Z合并产生的美元更新过程的“幂律P \ ' olya瓮”哈蒙德和谢菲尔德我们证明对分数布朗运动功能融合,关闭密封参数的纸的空白。此外,在强更新定理的范围内,我们深入了解了Hammond-Sheffield urn中的合并更新过程(例如最近共同祖先的渐近深度),并且能够控制从$[n]$中随机抽样的两个,三个和四个个体的合并概率。这允许我们获得一个新的,概念性的渐近高斯性(包括泛函收敛性)的更一般着色的重整化和的证明,它可以被看作是超越Hammond和Sheffield的主要结果的不变性原理。在这个证明中,一个独立感兴趣的关键因素是基于Stein方法的$[n]$随机着色随机分区中重整化和的渐近高斯性的充分判据。在此过程中,我们还证明了Blath, Gonz\ alez Casanova, Kurt和Span\ o的远程种子库模型中合并概率的渐近性。
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来源期刊
CiteScore
1.10
自引率
0.00%
发文量
48
期刊介绍: ALEA publishes research articles in probability theory, stochastic processes, mathematical statistics, and their applications. It publishes also review articles of subjects which developed considerably in recent years. All articles submitted go through a rigorous refereeing process by peers and are published immediately after accepted. ALEA is an electronic journal of the Latin-american probability and statistical community which provides open access to all of its content and uses only free programs. Authors are allowed to deposit their published article into their institutional repository, freely and with no embargo, as long as they acknowledge the source of the paper. ALEA is affiliated with the Institute of Mathematical Statistics.
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