Asymptotic genealogies for a class of generalized Wright-Fisher models
Abstract
We study a class of Cannings models with population size having a mixed multinomial offspring distribution with random success probabilities induced by independent and identically distributed positive random variables via , , where . The ancestral lineages are hence based on a sampling with replacement strategy from a random partition of the unit interval into subintervals of lengths . Convergence results for the genealogy of these Cannings models are provided under regularly varying assumptions on the tail distribution of . In the limit several coalescent processes with multiple and simultaneous multiple collisions occur. The results extend those obtained by Huillet (2014) for the case when is Pareto distributed and complement those obtained by Schweinsberg (2003) for models where one samples without replacement from a supercritical branching process.
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Cite
@article{arxiv.2106.10939,
title = {Asymptotic genealogies for a class of generalized Wright-Fisher models},
author = {Thierry Huillet and Martin Möhle},
journal= {arXiv preprint arXiv:2106.10939},
year = {2021}
}
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24 pages