Bayesian Predictive Inference and Related Asymptotics—Festschrift for Eugenio Regazzini's 75th Birthday

Dear Colleagues,

To make reliable predictions, based on observed data, is one of the major tasks in probability and statistics. To this end, the Bayesian approach is possibly the natural one. However, there are still various issues which need further investigation.  Just to mention a few: (i) In addition to exchangeability, what dependence structures are suitable for prediction ? (ii) Is it possible to make Bayesian predictions without involving the usual prior/posterior scheme ? (iii) What about the asymptotic behavior of predictive distributions ? (iv) In particular, what is the convergence rate of the distance between empirical and predictive measures ? This special issue aims to collect some recent papers on (i)-(iv) and related topics, paying special attention to the asymptotic problems.

Dr. Emanuele Dolera
Dr. Federico Bassetti
Guest Editors

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