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Title: Bayesian nonparametric inference with heterogeneous data Authors:  Antonio Lijoi - Bocconi University (Italy) [presenting]
Abstract: In the last few years, the analysis of non-exchangeable data has attracted considerable interest in the Bayesian nonparametric literature. The aim is to discuss a model based on dependent discrete random probability measures that may be used to deal with data that are generated under different, though related, experimental conditions. Predictive distributions and posterior characterizations will be presented, along with algorithms that allow to determine approximate Bayesian inferences of interest. The discussion will be completed by illustrations with simulated and real data.