Posterior Averaging Information Criterion

Posterior Averaging Information Criterion

We propose a new model selection method, named the posterior averaging information criterion, for Bayesian model assessment to minimize the risk of predicting independent future observations. The theoretical foundation is built on the Kullback–Leibler divergence to quantify the similarity between th...

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Bibliographic Details
Main Author: Shouhao Zhou
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Entropy
Subjects:
Bayesian modeling
expected out-of-sample likelihood
Kullback–Leibler divergence
misspecified model
predictive model selection
Online Access:https://www.mdpi.com/1099-4300/25/3/468

Internet

https://www.mdpi.com/1099-4300/25/3/468

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