Research lectures, seminars and events
The events listed in this area are research seminars, workshops and lectures hosted by Durham University departments and research institutes. If you are not a member of the University, but wish to enquire about attending one of the events please contact the organiser or host department.
Stats4Grads: Reducing bias is as easy as ABC
Approximate Bayesian Computation(ABC) has enabled us in recent years to use increasingly complex models to solve problems that were previously intractable. ABC methods can produce unreliable inference when they introduce high approximation bias into the posterior through careless specification of the ABC kernel. Additionally MCMC-ABC methods often suffer from the local trapping problem which causes poor mixing when the tolerance parameter is low. We propose an alternative ABC algorithm which we show can be used to reduce the approximation bias and provide immunity to local trapping by adaptively constructing the ABC kernel. We demonstrate the new algorithm on real data; calibrating a complex SEIR model to data from the Ebola outbreak of 2014 and estimating the pre intervention transmission rate of the disease.
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