Bayesian Monte Carlo testing with one-dimensional measures of evidence.

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorSilva, Ivair Ramos-
Autor(es): dc.creatorMarques, Reinaldo Antônio Gomes-
Data de aceite: dc.date.accessioned2025-08-21T15:31:43Z-
Data de disponibilização: dc.date.available2025-08-21T15:31:43Z-
Data de envio: dc.date.issued2019-06-06-
Data de envio: dc.date.issued2019-06-06-
Data de envio: dc.date.issued2019-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/handle/123456789/11455-
Fonte completa do material: dc.identifierhttps://www.sciencedirect.com/science/article/pii/S0377042718306964-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.cam.2018.11.016-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1017503-
Descrição: dc.descriptionBayesian hypothesis testing procedures are constructed by means of test statistics which are functions of the posterior distribution. Usually, the whole sample vector is selected to form the sufficient empirical part of the posterior distribution. But, in certain problems, one may prefer to use well-established one-dimensional sufficient statistics in place of the sample vector. This paper introduces a Bayesian Monte Carlo procedure specially designed for such cases. It is shown that the performance of this new approach is arbitrarily close to the exact Bayesian test. In addition, for arbitrary desired precisions, we develop a theoretical rule of thumb for choosing the minimum number m0 of Monte Carlo simulations. Surprisingly, m0 does not depend on the shape of loss/cost functions when those are used to compound the test statistic. The method is illustrated for testing mean vectors in highdimension and for detecting spatial clusters of diseases in aggregated maps.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsrestrito-
Palavras-chave: dc.subjectBayes factor-
Palavras-chave: dc.subjectExpected loss-
Palavras-chave: dc.subjectExact test-
Título: dc.titleBayesian Monte Carlo testing with one-dimensional measures of evidence.-
Aparece nas coleções:Repositório Institucional - UFOP

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