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SUMMARY:Efficient construction of optimal designs for stochastic kinetic m
 odels - Colin Gillespie (Newcastle University)
DTSTART:20160428T100000Z
DTEND:20160428T110000Z
UID:TALK66001@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Stochastic kinetic models are discrete valued continuous time 
  Markov processes and are often used to describe biological and  ecologica
 l systems. In recent years there has been interest in  the construction of
  Bayes optimal&nbsp\;experimental&nbsp\;designs&nbsp\;for these  models. U
 nfortunately standard methods such as that by  Muller (1999) are computati
 onally intensive even for relatively  simple models. However progress can 
 be made by using a sequence  of Muller algorithms\, where each one has an 
 increasing power of  the expected utility function as its marginal distrib
 ution. At  each stage efficient proposals in the&nbsp\;design&nbsp\;dimens
 ion can be  made using the results from the previous stages. In this talk 
 we  outline this algorithm\, investigate some computational efficiency  ga
 ins made using parallel computing and illustrate the results  with an exam
 ple.
LOCATION:Seminar Room 2\, Newton Institute
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