ANC Seminar: Chris Sherlock (Lancaster)
Lunch provided afterwards in MF2
What 


When 
May 24, 2016 from 11:00 AM to 12:00 PM 
Where  IF 4.31/4.33 
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Delayed acceptance [particle] MCMC for inference on reaction networks.
When conducting Bayesian inference, delayed acceptance (DA) MetropolisHastings (MH) algorithms and DA pseudomarginal MH algorithms can be applied when it is computationally expensive to calculate the true posterior or an unbiased estimate thereof, but a computationallycheap approximation is available. A first acceptreject stage is applied, with the cheap approximation substituted for the true posterior in the MH acceptance ratio. Only for those proposals which pass through the first stage is the computationally expensive true posterior (or unbiased estimate thereof) evaluated, with a second acceptreject stage ensuring that detailed balance is satisfied with respect to the intended true posterior. For some reaction networks the Linear Noise Approximation provides a cheap and relatively accurate approximation whereas in other scenarios there is no obvious computationallycheap surrogate. In such cases a weighted average of previous evaluations of the computationally expensive posterior provides a generic approximation. I will discuss inference for reaction networks using delayed acceptance MCMC in each of the above scenarios.