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Asymptotic genealogies for a class of generalized Wright-Fisher models

Probability 2021-10-01 v2

Abstract

We study a class of Cannings models with population size NN having a mixed multinomial offspring distribution with random success probabilities W1,,WNW_1,\ldots,W_N induced by independent and identically distributed positive random variables X1,X2,X_1,X_2,\ldots via Wi:=Xi/SNW_i:=X_i/S_N, i{1,,N}i\in\{1,\ldots,N\}, where SN:=X1++XNS_N:=X_1+\cdots+X_N. The ancestral lineages are hence based on a sampling with replacement strategy from a random partition of the unit interval into NN subintervals of lengths W1,,WNW_1,\ldots,W_N. Convergence results for the genealogy of these Cannings models are provided under regularly varying assumptions on the tail distribution of X1X_1. 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 X1X_1 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