Consistency and identifiability in Bayesian analysis
The importance of posterior consistency in the robustness of Bayesian analysis is examined and discussed. The notions of sufficient and minimal sufficient parameters are introduced and important consistency results for such parameters are derived. We see that minimal sufficient parameters are fundamental in characterising the relationship between data and parameters. The concept of identifiability is then introduced and several equivalent definitions are given. The relationship between...[Show more]
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