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SUMMARY:A particle filter for Bayesian sequential design - McGree\, J (Que
 ensland University of Technology)
DTSTART:20110830T110000Z
DTEND:20110830T113000Z
UID:TALK32747@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:A particle filter approach is presented for sequential design 
 with a focus on Bayesian adaptive dose finding studies for the estimation 
 of the maximum tolerable dose. The approach is computationally convenient 
 in that the information of newly observed data can be incorporated through
  a simple re-weighting step. Furthermore\, the method does not require pri
 or information represented as imagined data as in other dose finding appro
 aches\, although such data can be included straightforwardly if available.
  We also consider a flexible parametric model together with a newly develo
 ped hybrid design utility that can produce more robust estimates of the ta
 rget dose in the presence of substantial model and parameter uncertainty. 
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LOCATION:Seminar Room 1\, Newton Institute
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