Matching Priors for Prediction
In the preceding chapters, we considered probability matching priors for estimation. The object of interest was a parameter, either one-dimensional or multidimensional, and priors ensuring approximate frequentist validity of the associated posterior credible regions were studied. Evidently, the solutions for these matching priors depend on the specification of the interest parameter. For instance, in Example 2.5.7 concerning the Student’s t-model, it was seen that a unique second order matching prior exists when the location parameter θ1 is of interest whereas no such prior is available when interest lies in the shape parameter θ2.
KeywordsAuxiliary Variable Prediction Interval Future Observation Predictive Density Bayesian Prediction
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