Approximated Information Analysis in Bayesian Inference

In models with nuisance parameters, Bayesian procedures based on Markov Chain Monte Carlo (MCMC) methods have been developed to approximate the posterior distribution of the parameter of interest. Because these procedures require burdensome computations related to the use of MCMC, approximation and...

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Bibliographic Details
Main Authors: Jung In Seo, Yongku Kim
Format: Article
Language:English
Published: MDPI AG 2015-03-01
Series:Entropy
Subjects:
Online Access:http://www.mdpi.com/1099-4300/17/3/1441