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SUMMARY:Bayesian inference in continuous time jump processes - Godsill\, S
  (University of Cambridge)
DTSTART:20140116T133000Z
DTEND:20140116T141500Z
UID:TALK49982@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:In this talk I will discuss recent advances in inference for c
 ontinuous time processes with random changepoints or jumps. I will discuss
  cases with finite numbers of jumps\, modelled within a jump-diffusion or 
 piecewise deterministic processed framework\, then go on to describe proce
 sses with almost surely infinite numbers of jumps on finite intervals\, fo
 cussing on recent developments for alpha-stable Levy processes. Methodolog
 y is Bayesian\, using computational methods related to Markov chain Monte 
 Carlo and particle filtering. \n
LOCATION:Seminar Room 1\, Newton Institute
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