Information criteria for the predictive evaluation of bayesian models

DOI10.1080/03610929708832043zbMath0954.62528OpenAlexW2021070302MaRDI QIDQ4269958

Genshiro Kitagawa

Publication date: 10 November 1999

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929708832043

zbMATH Keywords

likelihoodKullback-Leibler informationAICbias correction

Mathematics Subject Classification ID

Bayesian inference (62F15) Statistical aspects of information-theoretic topics (62B10)

Related Items (4)

Inadmissibility of the corrected Akaike information criterion ⋮ Bayesian prediction and model selection for locally asymptotically mixed normal models ⋮ A variant of AIC based on the Bayesian marginal likelihood ⋮ Unnamed Item

Cites Work

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• Predictive likelihood
• On the use of the predictive likelihood of a Gaussian model
• Predictive likelihood: A review. With comments and a rejoinder by the author
• Density Estimation and Bump-Hunting by the Penalized Likelihood Method Exemplified by Scattering and Meteorite Data
• SEASONAL ADJUSTMENT BY A BAYESIAN MODELING
• Further analysis of the data by Akaike's information criterion and the finite corrections
• Generalised information criteria in model selection

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