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arXiv 2011.06908math.PR

尺度化跳跃链与 Kingman 溯祖突变数的弱收敛

Weak convergence of the scaled jump chain and number of mutations of the Kingman coalescent

Martina Favero, Henrik Hult

AI总结:

本文研究大样本下 Kingman 溯祖的块计数与突变计数链,证明其尺度化后分别弱收敛至确定性过程和变强度 Poisson 过程,并用测度变换推广到亲本依赖突变。

摘要:

Kingman 溯祖是群体遗传学中的一个基本过程,用于沿时间逆向模拟一个个体样本的祖先谱系。本文在大样本量情形下,研究该溯祖在中性假设及一般有限等位基因突变机制下的渐近性质,即同时包含亲本独立突变与亲本依赖突变。具体而言,我们考虑一列与该溯祖相关的 Markov 链,其由块计数和突变计数两个组成部分构成。我们证明,这些组成部分经过适当尺度化后,分别弱收敛于确定性组成部分和具有变化强度的 Poisson 过程。在此过程中,我们发展了一种基于测度变换的新方法,将收敛结果从亲本独立突变情形推广到亲本依赖突变情形;在后一情形中,若干关键量并不能显式得到。

英文摘要:

The Kingman coalescent is a fundamental process in population genetics modelling the ancestry of a sample of individuals backwards in time. In this paper, in a large-sample-size regime, we study asymptotic properties of the coalescent under neutrality and a general finite-alleles mutation scheme, i.e. including both parent independent and parent dependent mutation. In particular, we consider a sequence of Markov chains that is related to the coalescent and consists of block-counting and mutation-counting components. We show that these components, suitably scaled, converge weakly to deterministic components and Poisson processes with varying intensities, respectively. Along the way, we develop a novel approach, based on a change of measure, to generalise the convergence result from the parent independent to the parent dependent mutation setting, in which several crucial quantities are not known explicitly.

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