Ajay Jasra (Imperial College London)

The Time Machine: A Simulation Approach for Stochastic Trees 

One of the most important areas in computational genetics is the calculation and subsequent maximization of the likelihood function associated to such models. This typically consists of using importance sampling  and sequential Monte Carlo techniques. The approach proceeds by simulating, backward in time from observed data, to a most recent common ancestor.

However, in many cases, the computational time and variance of estimators are often too high to make standard approaches useful. In this talk I propose to stop the simulation, subsequently yielding biased estimates of the likelihood surface.  The bias investigated from a theoretical point of view. Also, extensive simulation results are given, which justify the loss of accuracy with significant savings in computational time. This is a joint work with Maria De Iorio and Marc Chadeau-Hyam.