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Bayesian Nonparametric Inference for Random Distributions and Related Functions
1999
Journal of The Royal Statistical Society Series B-statistical Methodology
In recent years, Bayesian nonparametric inference, both theoretical and computational, has witnessed considerable advances. However, these advances have not received a full critical and comparative analysis of their scope, impact and limitations in statistical modelling; many aspects of the theory and methods remain a mystery to practitioners and many open questions remain. In this paper, we discuss and illustrate the rich modelling and analytic possibilities that are available to the
doi:10.1111/1467-9868.00190
fatcat:ji4zf5u57vapfkpcupeg6ph3bm