Bayesian Inference Under Partial Prior Information

Elias Moreno, Francesco Bertolino and Walter Racugno

Scandinavian Journal of Statistics, 2003, vol. 30, issue 3, 565-580

Abstract: Partial prior information on the marginal distribution of an observable random variable is considered. When this information is incorporated into the statistical analysis of an assumed parametric model, the posterior inference is typically non‐robust so that no inferential conclusion is obtained. To overcome this difficulty a method based on the standard default prior associated to the model and an intrinsic procedure is proposed. Posterior robustness of the resulting inferences is analysed and some illustrative examples are provided.

Date: 2003
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