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Department of Mathematical Sciences

Seminars

This week's seminars

Statistics Seminars: ABC for expensive simulators

Presented by Richard Everitt, University of reading

26 February 2018 14:00 in CM221

Approximate Bayesian computation (ABC) is now an established technique for statistical inference in the form of a simulator, and approximates the likelihood at a parameter θ by simulating auxiliary data sets x and evaluating the distance of x from the true data y. Synthetic likelihood is a related approach that uses simulated auxiliary data sets to contract a Gaussian approximation to the likelihood. However, these approaches are not computationally feasible in cases where using the simulator for each θ is very expensive. This talk investigates two alternative strategies for inference in such a situation. The first is delayed acceptance ABC-SMC (arxiv.org/abs/1708.02230), in which a cheap simulator is used to rule out parts of the parameter space that are not worth exploring. The second is bootstrapped synthetic likelihood (arxiv.org/abs/1711.05825), which uses the bootstrap to cheaply estimate the synthetic likelihood. We also examine a synthetic likelihood approximation that is constructed, using the bag of little bootstraps, from subsampled data sets. Applications to stochastic differential equation models and doubly intractable distributions will be presented.


Contact sunil.chhita@durham.ac.uk for more information

Research Seminars by Series

The research groups in the Department of Mathematical Sciences hold several seminar series in term time. Information on date, time and location are available here.

For information on previous years' seminars please see the seminar archives pages.