A Bayesian Large Deviations Probabilistic Interpretation and Justification of Empirical Likelihood

Marian Grendar and George Judge ()

No 7191, CUDARE Working Papers from University of California, Berkeley, Department of Agricultural and Resource Economics

Abstract: In this paper we demonstrate, in a parametric Estimating Equations setting, that the Empirical Likelihood (EL) method is an asymptotic instance of the Bayesian non-parametric Maximum-A-Posteriori approach. The resulting probabilistic interpretation and justifcation of EL rests on Bayesian non-parametric consistency in L-divergence.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 12
Date: 2007
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: A Bayesian Large Deviations Probabilistic Interpretation and Justification of Empirical Likelihood (2007)
Working Paper: A Bayesian large deviations probabilistic interpretation and justification of empirical likelihood (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:ucbecw:7191

DOI: 10.22004/ag.econ.7191

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