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University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > A nested particle filter for online Bayesian parameter estimation in state-space systems

## A nested particle filter for online Bayesian parameter estimation in state-space systemsAdd to your list(s) Download to your calendar using vCal - Miguez, J (Universidad Carlos III de Madrid)
- Wednesday 30 April 2014, 11:30-12:30
- Seminar Room 2, Newton Institute Gatehouse.
If you have a question about this talk, please contact Mustapha Amrani. Advanced Monte Carlo Methods for Complex Inference Problems We address the problem of approximating the probability measure of the fixed parameters of a state-space dynamic system using a sequential Monte Carlo method (SMC). The proposed approach relies on a nested structure that employs two layers of particle filters to approximate the posterior probability law of the static parameters and the dynamic variables of the system of interest, in the vein of the recent SMC This talk is part of the Isaac Newton Institute Seminar Series series. ## This talk is included in these lists:- All CMS events
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