Bayesian Predictive Inference and Related Asymptotics-Festschrift for Eugenio Regazzini's 75th Birthday / / edited by Emanuele Dolera and Federico Bassetti.

• TeilnehmendeR: Dolera, Emanuele,; Bassetti, Federico,
• Place / Publishing House: Basel : : MDPI - Multidisciplinary Digital Publishing Institute,, 2022.
• Year of Publication: 2022
• Language: English
• Physical Description: 1 online resource (198 pages)

Bayesian predictive inference is at the core of the mathematical theory of inductive reasoning. Nowadays, this field has become very attractive especially for its connections with algorithmic probability, machine learning and artificial intelligence. The complexity of both problems and algorithm represents a constant source of research of asymptotic techniques, which are necessary to handle vast datasets. The present book contains the 11 papers accepted and published in the Special Issue "Bayesian Predictive Inference and Related Asymptotics-Festschrift for Eugenio Regazzini's 75th Birthday" of the MDPI Mathematics journal. The topics of the paper focus, among others, on Bayesian nonparametrics, species sampling models, partial exchangeability and optimal stopping. Finally, as the title suggests, the Special Issue aims to celebrate the 75th birthday of Prof. Eugenio Regazzini, who has provided so many important contributions to the field of Bayesian inference.

Table of Contents

Preface to the Special Issue on "Bayesian Predictive Inference and Related -- Asymptotics-Festschrift for Eugenio Regazzini's 75th Birthday" -- A Compound Poisson Perspective of Ewens-Pitman Sampling Model -- Predictive Constructions Based on Measure-Valued Polya Urn Processes ´ -- On Johnson's "Sufficientness" Postulates for Feature-Sampling Models -- The Rescaled Polya Urn and the Wright-Fisher Process with Mutation ´ -- Mixture of Species Sampling Models -- A Central Limit Theorem for Predictive Distributions -- Trapping the Ultimate Success -- Partial Exchangeability for Contingency Tables -- Single-Block Recursive Poisson-Dirichlet Fragmentations of Normalized Generalized Gamma Processes -- Asymptotic Efficiency of Point Estimators in Bayesian Predictive Inference -- Fisher, Bayes,and Predictive Inference.