Large Deviations Approach to Bayesian Nonparametric Consistency: the Case of Polya Urn Sampling

Marian Grendar, George Judge () and R.K. Niven

No 6056, CUDARE Working Papers from University of California, Berkeley, Department of Agricultural and Resource Economics

Abstract: The Bayesian Sanov Theorem (BST) identifies, under both correct and incorrect specification of infinite dimensional model, the points of concentration of the posterior measure. Utilizing this insight in the context of Polya urn sampling, Bayesian nonparametric consistency is established. Polya BST is also used to provide an extension of Maximum Non-parametric Likelihood and Empirical Likelihood methods to the Polya case.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 6
Date: 2007
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Working Paper: Large Deviations Approach to Bayesian Nonparametric Consistency: the Case of Polya Urn Sampling (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:ucbecw:6056

DOI: 10.22004/ag.econ.6056

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