Sufficientness postulates for Gibbs-type priors and hierarchical generalizations

DOI10.1214/17-STS619zbMath1383.62079OpenAlexW2769635192MaRDI QIDQ1704698

Lorenzo Trippa, Sergio Bacallado, Marco Battiston, Stefano Favaro

Publication date: 13 March 2018

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ss/1511838024

zbMATH Keywords

Bayesian nonparametricsdiscovery probabilityDirichlet and two parameter Poisson-Dirichlet processGibbs-type species sampling modelshierarchical species sampling modelsJohnson's ``sufficientness postulatePólya-like urn schemepredictive probabilities

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Bayesian inference (62F15)

Related Items (6)

Scaled Process Priors for Bayesian Nonparametric Estimation of the Unseen Genetic Variation ⋮ Sufficientness postulates for Gibbs-type priors and hierarchical generalizations ⋮ Hierarchical species sampling models ⋮ Approximating predictive probabilities of Gibbs-type priors ⋮ Bayesian nonparametric disclosure risk assessment ⋮ Gibbs partitions, Riemann–Liouville fractional operators, Mittag–Leffler functions, and fragmentations derived from stable subordinators

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