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6 March 2020
Europe/Stockholm timezone

Importance sampling and weak convergence in population genetics

6 Mar 2020, 14:00
4001 (Ångströmslaboratoriet)




Martina Favero (KTH)


Importance sampling algorithms are used in population genetics to estimate small probabilities of gene configurations. ​In order to prove the efficiency of these algorithms, it is necessary to determine the asymptotic behaviour of the sampling probabilities. As a first step in this direction, we show weak convergence for a sequence of coalescent processes and the corresponding mutation processes, as the sample size goes to infinity. Time is scaled and convergence of semigroups is proved. The limiting process consists of a deterministic part and of conditionally independent Poisson processes with varying intensity. This is a work in progress with H.Hult (KTH)​.

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