The INI has a new website!

This is a legacy webpage. Please visit the new site to ensure you are seeing up to date information.

Skip to content



Bayesian inference for nonlinear multivariate diffusion processes

Wilkinson, D (Newcastle)
Thursday 02 November 2006, 15:45-17:00

Seminar Room 1, Newton Institute


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.


[pdf ]



Back to top ∧