A note on the solution of the intrinsic equations
- Cano Sánchez, Juan Antonio
- Kessler, Mathieu
- Moreno Bas, Elías
Publisher: Jaén : Universidad de Jaén, 2001
ISBN: 84-8439-080-2
Year of publication: 2001
Congress: Congreso Nacional de Estadística e Investigación Operativa (26. 2001. Úbeda)
Type: Conference paper
Abstract
Defaults priors are topically used in Bayesian inference when there is no subjective information on the unknown parameters. In model selection and prediction the conventional default priors are not suitable because they are improper. However, they can be converted in appropiate priors via the solution of the functional intrinsic equations introduced in Berger and Pericchi (1996) and partially studied in Moreno, Bertolino and Racugno (1998). While the solution to these equations is known for nested models, to establishing conditions to characterize the solution for non-nested models is still an open problem. In this paper we push forward this problem and give illustrations of the obtained results