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Type: Artigo de periódico
Title: Full Bayesian significance test for extremal distributions
Author: de Bernardini, DF
Rifo, LLR
Abstract: A new Bayesian measure of evidence is used for model choice within the generalized extreme value family of distributions, given an absolutely continuous posterior distribution on the related parametric space. This criterion allows quantitative measurement of evidence of any sharp hypothesis, with no need of a prior distribution assignment to it. We apply this methodology to the testing of the precise hypothesis given by the Gumbel model using real data. Performance is compared with usual evidence measures, such as Bayes factor, Bayesian information criterion, deviance information criterion and descriptive level for deviance statistic.
Subject: Bayesian inference
credible intervals
extremal-type distribution
full Bayesian significance test
predictive return level
Country: Inglaterra
Editor: Taylor & Francis Ltd
Citation: Journal Of Applied Statistics. Taylor & Francis Ltd, v. 38, n. 4, n. 851, n. 863, 2011.
Rights: fechado
Identifier DOI: 10.1080/02664761003692340
Date Issue: 2011
Appears in Collections:Unicamp - Artigos e Outros Documentos

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