Asymptotic genealogies for a class of generalized Wright–Fisher models

IF 0.7 Q3 STATISTICS & PROBABILITY Modern Stochastics-Theory and Applications Pub Date : 2021-06-21 DOI:10.15559/21-vmsta196
T. Huillet, M. Möhle
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引用次数: 5

Abstract

We study a class of Cannings models with population size N having a mixed multinomial offspring distribution with random success probabilities W1, . . . ,WN induced by independent and identically distributed positive random variables X1, X2, . . . via Wi := Xi/SN , i ∈ {1, . . . , N}, where SN := X1 + · · · + XN . The ancestral lineages are hence based on a sampling with replacement strategy from a random partition of the unit interval into N subintervals of lengths W1, . . . ,WN . Convergence results for the genealogy of these Cannings models are provided under regularly varying assumptions on the tail distribution of X1. In the limit several coalescent processes with multiple and simultaneous multiple collisions occur. The results extend those obtained in [15] for the case when X1 is Pareto distributed and complement those obtained in [37] for models where one samples without replacement from a supercritical branching process.
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一类广义Wright-Fisher模型的渐近谱系
研究了一类总体大小为N的canings模型,其子代分布为混合多项,成功概率为随机概率W1,。,由独立的同分布的正随机变量X1, X2,…, N},其中SN:= X1 +···+ XN。因此,祖先谱系是基于从单位区间随机划分为长度为W1,…的N个子区间的替换策略的抽样。, WN。在X1尾部分布的规则变化假设下,给出了这些坎宁模型谱系的收敛结果。在极限条件下,会发生多个同时发生多次碰撞的聚结过程。在X1为帕累托分布的情况下,结果扩展了[15]中的结果,并补充了[37]中对超临界分支过程中一个样本没有替换的模型的结果。
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来源期刊
Modern Stochastics-Theory and Applications
Modern Stochastics-Theory and Applications STATISTICS & PROBABILITY-
CiteScore
1.30
自引率
50.00%
发文量
0
审稿时长
10 weeks
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