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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Detalles Bibliográficos
Autor principal: Zhou, Shouhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047922/
https://www.ncbi.nlm.nih.gov/pubmed/36981356
http://dx.doi.org/10.3390/e25030468

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047922/
https://www.ncbi.nlm.nih.gov/pubmed/36981356
http://dx.doi.org/10.3390/e25030468

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