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

• Format: eBook
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Subjects: Mathematics & science; Research & information: general; algebraic statistics; asymptotic efficiency; Bayesian inference; Bayesian nonparametrics; bayesian predictive inference; Berry-Esseen type theorem; best choice problem; central limit theorem; compatibility equations; conditional identity in distribution; contingency tables; de Finetti representation theorem; de Finetti theorem; de Finetti's representation theorem; decision theory; Ewens-Pitman sampling model; exchangeability; exchangeable random partitions; exchangeable sequences; feature-sampling model; Fisher fiducial argument; fragmentations of mass partitions; generalized gamma process; inverse probability; Johnson's "sufficientness" postulate; last record; log-series compound poisson sampling model; Markov basis; Mittag-Leffler distribution function; Mittag-Leffler Markov Chains; n/a; negative binomial compound poisson sampling model; optimal stopping time; partial exchangeability; Pitman's α-diversity; Poisson-Dirichlet distributions; Pólya sequences; Pólya urn; predictive distribution; predictive distributions; predictive mean; random probability measures; reinforced processes; scaled process prior; species sampling; species sampling models; species-sampling model; stable convergence; total variation distance; trapping strategy; uniform distribution; urn model; urn schemes; Wasserstein distance; wright distribution function; Wright-Fisher diffusion
• Online Access: Open Access: DOAB: description of the publication; Open Access: DOAB, download the publication
• Physical Description: 1 online resource (198 p.)
• ISBN: 9783036551135; 9783036551142; books978-3-0365-5114-2
• Access: Open Access

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.