Data Assimilation Meetings at Reading

Date Meeting type Speakers
5 February 2014 Internal speaker Dennis Prangle (University of Reading)
Approximate Bayesian Computation and Particle Filters. (pdf)
Approximate Bayesian computation (ABC) methods perform approximate statistical inference for a class of otherwise intractable problems. The approach is that data are simulated for various parameter values and inference is based on those parameter values whose simulations are close matches to the observed data. Simple ABC algorithms often perform poorly for high dimensional data. In some settings these problems can be avoided by using ABC ideas within particle filter methodology. This talk is a review of recent work on this approach.

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