Paul A. Jenkins, Dario Spano
(Submitted on 23 Jun 2015)
The Wright-Fisher family of diffusion processes is a class of evolutionary models widely used in population genetics, with applications also in finance and Bayesian statistics. Simulation and inference from these diffusions is therefore of widespread interest. However, simulating a Wright-Fisher diffusion is difficult because there is no known closed-form formula for its transition function. In this article we demonstrate that it is in fact possible to simulate exactly from the scalar Wright-Fisher diffusion with general drift, extending ideas based on retrospective simulation. Our key idea is to exploit an eigenfunction expansion representation of the transition function. This approach also yields methods for exact simulation from several processes related to the Wright-Fisher diffusion: (i) its moment dual, the ancestral process of an infinite-leaf Kingman coalescent tree; (ii) its infinite-dimensional counterpart, the Fleming-Viot process; and (iii) its bridges. Finally, we illustrate our method with an application to an evolutionary model for mutation and diploid selection. We believe our new perspective on diffusion simulation holds promise for other models admitting a transition eigenfunction expansion.