The Best Fit Bayesian Hierarchical Generalized Linear Model Selection Using Information Complexity Criteria in the MCMC Approach

The Best Fit Bayesian Hierarchical Generalized Linear Model Selection Using Information Complexity Criteria in the MCMC Approach

Both frequentist and Bayesian statistics schools have improved statistical tools and model choices for the collected data or measurements. Model selection approaches have advanced due to the difficulty of comparing complicated hierarchical models in which linear predictors vary by grouping variables...

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Bibliographic Details
Main Authors:	Endris Assen Ebrahim, Mehmet Ali Cengiz, Erol Terzi
Format:	Article
Language:	English
Published:	Hindawi Limited 2024-01-01
Series:	Journal of Mathematics
Online Access:	http://dx.doi.org/10.1155/2024/1459524

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