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A generalization of Jeffreys' rule for non regular models

 

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Opened Access A generalization of Jeffreys' rule for non regular models
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Author: Ortega, Francisco J.
Basulto Santos, Jesús
Department: Universidad de Sevilla. Departamento de Economía Aplicada I
Date: 2016
Published in: Communications in Statistics - Theory and Methods, 45 (15), 4433-4444.
Document type: Article
Abstract: We propose a generalization of the one-dimensional Jeffreys’ rule in order to obtain non informative prior distributions for non regular mod- els, taking into account the comments made by Jeffreys in his arti- cle 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 infer- ence problem and also avoids the problem that the maximum likelihood estimator has with these models. Finally, we obtain non informative dis- tributions in job-search and deterministic frontier production homoge- nous models
Cite: Ortega, F.J. y Basulto Santos, J. (2016). A generalization of Jeffreys' rule for non regular models. Communications in Statistics - Theory and Methods, 45 (15), 4433-4444.
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URI: https://hdl.handle.net/11441/70566

DOI: 10.1080/03610926.2014.921303

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