Posterior predictive scimulation Checks for hierarchical Bayesian Modelling - M. Elobaid, Rafida; Ibrahim, Noor Akma (CESER Publications, 2010)
Problem statement: Assessing the plausibility of a posited model is always fundamental in order to evaluate and examine its performance. Such assessment is essential in the field of Bayesian data analysis. A Bayesian analysis can be very misleading when the model is far from plausible. Thus, any Bayesian analysis should include an evaluation method to find out whether the posited model should be excluded because it fails to provide a reasonable summary of the data at hand. Such evaluation method is referred as the posterior predictive checks.