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

• Andere auteurs: Dolera, Emanuele (Redacteur), Bassetti, Federico (Redacteur)
• Formaat: Elektronisch Hoofdstuk
• Taal: Engels
• Gepubliceerd in: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Onderwerpen: Research & information: general; Mathematics & science; 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 sequences; bayesian predictive inference; central limit theorem; 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; compatibility equations; decision theory; de Finetti's representation theorem; Wasserstein distance; Fisher fiducial argument; inverse probability; uniform distribution; n/a
• Online toegang: DOAB: download the publication; DOAB: description of the publication

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 rep...