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SUMMARY:Bayesian nonparametrics with heterogeneous data - Antonio Lijoi\, 
 University of Pavia
DTSTART:20150130T160000Z
DTEND:20150130T170000Z
UID:TALK55751@talks.cam.ac.uk
CONTACT:20082
DESCRIPTION:The talk surveys some recent work on random probability measur
 e vectors and their role in Bayesian statistics. Indeed\, dependent nonpar
 ametric priors are useful tools for drawing inferences on data that arise 
 from different studies or experiments and for which the usual exhangeabili
 ty assumption is not satisfied. The presentation will focus on mixture mod
 els and their uses for density estimation and for the analysis of right-ce
 nsored survival data. Some of the theoretical results to be presented are 
 also relevant for devising Gibbs sampling schemes that will be applied to 
 simulated and real datasets.
LOCATION:MR12\,  Centre for Mathematical Sciences\, Wilberforce Road\, Cam
 bridge
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