The two-parameter Poisson–Dirichlet diffusion, introduced in 2009 by Petrov, extends the infinitely-many-neutral-alleles diffusion model, related to Kingman’s one-parameter Poisson–Dirichlet distribution and to certain Fleming–Viot processes. The additional parameter has been shown to regulate the clustering structure of the population, but is yet to be fully understood in the way it governs the reproductive process. Here, we shed some light on these dynamics by formulating a K-allele Wright–Fisher model for a population of size N, involving a uniform mutation pattern and a specific state-dependent migration mechanism. Suitably scaled, this process converges in distribution to a K-dimensional diffusion process as N → ∞. Moreover, the descend- ing order statistics of the K-dimensional diffusion converge in distri- bution to the two-parameter Poisson–Dirichlet diffusion as K → ∞. The choice of the migration mechanism depends on a delicate bal- ance between reinforcement and redistributive effects. The proof of convergence to the infinite-dimensional diffusion is nontrivial because the generators do not converge on a core. Our strategy for overcom- ing this complication is to prove a priori that in the limit there is no “loss of mass”, that is, that, for each limit point of the sequence of finite-dimensional diffusions (after a reordering of components by size), allele frequencies sum to one.

Wright-Fisher construction of the two-parameter Poisson-Dirichlet diffusion

COSTANTINI, CRISTINA;De Blasi, Pierpaolo;Ruggiero, Matteo;
2017-01-01

Abstract

The two-parameter Poisson–Dirichlet diffusion, introduced in 2009 by Petrov, extends the infinitely-many-neutral-alleles diffusion model, related to Kingman’s one-parameter Poisson–Dirichlet distribution and to certain Fleming–Viot processes. The additional parameter has been shown to regulate the clustering structure of the population, but is yet to be fully understood in the way it governs the reproductive process. Here, we shed some light on these dynamics by formulating a K-allele Wright–Fisher model for a population of size N, involving a uniform mutation pattern and a specific state-dependent migration mechanism. Suitably scaled, this process converges in distribution to a K-dimensional diffusion process as N → ∞. Moreover, the descend- ing order statistics of the K-dimensional diffusion converge in distri- bution to the two-parameter Poisson–Dirichlet diffusion as K → ∞. The choice of the migration mechanism depends on a delicate bal- ance between reinforcement and redistributive effects. The proof of convergence to the infinite-dimensional diffusion is nontrivial because the generators do not converge on a core. Our strategy for overcom- ing this complication is to prove a priori that in the limit there is no “loss of mass”, that is, that, for each limit point of the sequence of finite-dimensional diffusions (after a reordering of components by size), allele frequencies sum to one.
2017
27
3
1923
1950
http://projecteuclid.org/download/pdfview_1/euclid.aoap/1500451247
https://arxiv.org/pdf/1601.06064v3.pdf
Infinite-dimensional diffusion process; Migration; Reinforcement; Two-parameter Poisson-Dirichlet distribution; Weak convergence; Wright-Fisher model; Statistics and Probability; Statistics, Probability and Uncertainty
Costantini, Cristina; De Blasi, Pierpaolo; Ethier, Stewart N.; Ruggiero, Matteo; Spaç¹, Dario
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1654946
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