Data/hora: 13/06/2024 06:30:33

Provedor de dados: | 31
País: | United States
Título: | Large Deviations Approach to Bayesian Nonparametric Consistency: the Case of Polya Urn Sampling
Autores: | Grendar,   Marian; Judge,   George G.; Niven,   R.K.
Data: | 2008-05-09
Ano: | 2007
Palavras-chave: | Polya L-divergence; Bayesian maximum (A posterior); Probability method; Maximum Non-Parametric Likelihood method; Empirical likelihood method; Research Methods/ Statistical Methods.
Resumo: | 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.
Tipo: | Working or Discussion Paper
Idioma: | Inglês

Identificador:

29683

http://purl.umn.edu/6056

Relação:

University of California, Berkeley&gt;Department of Agricultural and Resource Economics&gt;CUDARE Working Papers

CUDARE Working Paper

1048

Formato: | 6