A generalization of Jeffreys' rule for non regular models. Issue 15 (2nd August 2016)

• Record Type: Journal Article
• Authors: Ortega, Francisco J.; Basulto, Jesús
• Is Part Of: Communications in statistics. Volume 45:Issue 15(2016)
• Page Start: 4433
• Page End: 4444
• Publication Date: 2016-08-02
• Subjects: Bayesian inference -- non informative prior distributions -- non regular models; 62F15; C11 -- C24; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2014.921303
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: We propose a generalization of the one-dimensional Jeffreys' rule in order to obtain non informative prior distributions for non regular models, taking into account the comments made by Jeffreys in his article of 1946. These non informatives are parameterization invariant and the Bayesian intervals have good behavior in frequentist inference. In some important cases, we can generate non informative distributions for multi-parameter models with non regular parameters. In non regular models, the Bayesian method offers a satisfactory solution to the inference problem and also avoids the problem that the maximum likelihood estimator has with these models. Finally, we obtain non informative distributions in job-search and deterministic frontier production homogenous models.