Frequentist-bayesian Monte Carlo testing.

Silva, Ivair Ramos; Marques, Reinaldo Antônio Gomes

Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/jspui/handle/123456789/12603

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DC Field	Value	Language
dc.contributor.author	Silva, Ivair Ramos	-
dc.contributor.author	Marques, Reinaldo Antônio Gomes	-
dc.date.accessioned	2020-08-17T14:01:56Z	-
dc.date.available	2020-08-17T14:01:56Z	-
dc.date.issued	2019	-
dc.identifier.citation	SILVA, I. R.; MARQUES, R. A. G. Frequentist-bayesian Monte Carlo testing. Communications in Statistics-Theory and Methods, v. 49, n. 10, fev. 2019. Disponível em: <https://www.tandfonline.com/doi/abs/10.1080/03610926.2019.1571610?af=R&journalCode=lsta20>. Acesso em: 03 jul. 2020.	pt_BR
dc.identifier.issn	1532-415X	-
dc.identifier.uri	http://www.repositorio.ufop.br/handle/123456789/12603	-
dc.description.abstract	Conventional methods for statistical hypothesis testing has historically been categorized as frequentist or Bayesian. But, a third option based on a reconciling hybrid frequentist-Bayesian framework is quickly emerging. Although prominent, there are applications where the exact hybrid test is not computable. For such cases, the present paper introduces a straightforward Monte Carlo procedure for performing frequentist-Bayesian testing.	pt_BR
dc.language.iso	en_US	pt_BR
dc.rights	restrito	pt_BR
dc.subject	Measure of evidence	pt_BR
dc.subject	Validity	pt_BR
dc.subject	Composite p-value	pt_BR
dc.title	Frequentist-bayesian Monte Carlo testing.	pt_BR
dc.type	Artigo publicado em periodico	pt_BR
dc.identifier.uri2	https://www.tandfonline.com/doi/abs/10.1080/03610926.2019.1571610?af=R&journalCode=lsta20	pt_BR
dc.identifier.doi	https://doi.org/10.1080/03610926.2019.1571610	pt_BR
Appears in Collections:	DEEST - Artigos publicados em periódicos

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