Reprint

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

Edited by
October 2022
198 pages
  • ISBN978-3-0365-5113-5 (Hardback)
  • ISBN978-3-0365-5114-2 (PDF)

This book is a reprint of the Special Issue Bayesian Predictive Inference and Related Asymptotics—Festschrift for Eugenio Regazzini's 75th Birthday that was published in

Computer Science & Mathematics
Engineering
Physical Sciences
Public Health & Healthcare
Summary

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.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
Berry–Esseen type theorem; Ewens–Pitman sampling model; exchangeable random partitions; log-series compound poisson sampling model; Mittag–Leffler distribution function; negative binomial compound poisson sampling model; Pitman’s α-diversity; wright distribution function; predictive distributions; random probability measures; reinforced processes; Pólya sequences; urn schemes; Bayesian inference; conditional identity in distribution; total variation distance; Bayesian nonparametrics; exchangeability; feature-sampling model; de Finetti theorem; Johnson’s “sufficientness” postulate; predictive distribution; scaled process prior; species-sampling model; Pólya urn; predictive mean; urn model; Wright—Fisher diffusion; species sampling models; exchangeable random partitions; exchangeable sequences; predictive distributions; bayesian predictive inference; central limit theorem; conditional identity in distribution; exchangeability; predictive distribution; stable convergence; best choice problem; optimal stopping time; last record; trapping strategy; algebraic statistics; contingency tables; de Finetti representation theorem; Markov basis; partial exchangeability; fragmentations of mass partitions; generalized gamma process; Mittag-Leffler Markov Chains; Poisson—Dirichlet distributions; species sampling; asymptotic efficiency; bayesian predictive inference; compatibility equations; decision theory; de Finetti’s representation theorem; exchangeability; Wasserstein distance; Bayesian inference; Fisher fiducial argument; inverse probability; uniform distribution; n/a