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SUMMARY:Introduction to Bayesian contraction rates - Kweku Abraham (Univer
 sity of Cambridge)
DTSTART:20170510T153000Z
DTEND:20170510T163000Z
UID:TALK72588@talks.cam.ac.uk
CONTACT:Nicolai Baldin
DESCRIPTION:Statisticians divide into two broad schools: *frequentists*\, 
 who assume there is a fixed but unknown process governing observed data\, 
 and *Bayesians*\, for whom statistics is about modelling our beliefs and u
 pdating sensibly when we see data. The Bayesian methodology has many attra
 ctive properties\, for example that essentially the same method is used in
  any possible set-up. But one can ask how well this method works if there 
 is indeed a fixed process governing the data\; this is the goal of *freque
 ntist analysis of Bayesian procedures*. I will provide a gentle introducti
 on to this field\, with reference made throughout to the specific problem 
 I'm researching\, that of finding posterior contraction rates (i.e. how fa
 st a Bayesian's beliefs converge to the truth) for estimation in stochasti
 c diffusion models.
LOCATION:MR14\, Centre for Mathematical Sciences
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