2:00 pm Thursday, May 21, 2015
Statistics: Bayesian Nonparametrics with Heterogeneous Data by
Antonio Lijoi [mail] (Univ Pavia) in GDC 7.402
The talk surveys some recent work on random probability measure vectors and their role in Bayesian statistics. Indeed, dependent nonparametric priors are useful tools for drawing inferences on data that arise from different studies or experiments and for which the usual exchangeability assumption is not realistic. The specific proposal that will be displayed gives rise to dependent discrete random probability measures and the talk will focus on their application to the analysis of right-censored survival data and to species sampling problems. The theoretical results to be presented are also relevant for devising Gibbs sampling schemes that will be applied to simulated and real datasets. Submitted by
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