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Bayesian inference for nonlinear multivariate diffusion processes

Presented by: 
D Wilkinson [Newcastle]
Thursday 2nd November 2006 - 15:45 to 17:00
INI Seminar Room 1

In this talk I will give an overview of the problem of conducting Bayesian inference for the fixed parameters of nonlinear multivariate diffusion processes observed partially, discretely, and possibly with error. I will present a sequential strategy based on either SIR or MCMC-based filtering for approximate diffusion bridges, and a "global" MCMC algorithm that does not degenerate as the degree of data augmentation increases. The relationship of these techniques to methods of approximate Bayesian computation will be highlighted.

University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons