Consistency of Empirical Likelihood and Maximum A-Posteriori Probability Under Misspecification

Marian Grendar and George Judge ()

Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series from Department of Agricultural & Resource Economics, UC Berkeley

Abstract: Using a large deviations approach, Maximum A-Posteriori Probability (MAP) and Empirical Likelihood (EL) are shown to possess, under misspecification, an exclusive property of Bayesian consistency. Under conditions of consistency, regardless of prior the MAP estimator asymptotically coincides with EL. The consistency property is also studied for sampling processes other than iid.

Keywords: Maximum Non-parametric Likelihood; estimating equations; Bayesian nonparametric consistency; Bayesian Large Deviations; L-divergence; Polya sampling; right censoring (search for similar items in EconPapers)
Date: 2008-02-20
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.escholarship.org/uc/item/4b78z47x.pdf;origin=repeccitec (application/pdf)

Related works:
Working Paper: Consistency of Empirical Likelihood and Maximum A-Posteriori Probability Under Misspecification (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cdl:agrebk:qt4b78z47x

Access Statistics for this paper

More papers in Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series from Department of Agricultural & Resource Economics, UC Berkeley Contact information at EDIRC.
Bibliographic data for series maintained by Lisa Schiff ().