Analysis and comparison of Bayesian methods for type A uncertainty evaluation with prior knowledge

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dc.contributor.authorLira, I.
dc.date.accessioned2025-01-20T21:00:39Z
dc.date.available2025-01-20T21:00:39Z
dc.date.issued2022
dc.description.abstractIf a number of observations about a certain quantity may be assumed independent, drawn from a Gaussian distribution, Supplement 1 to the GUM recommends that the standard uncertainty associated with the quantity be obtained by a formula that is applied to more than three observations. Various articles have recently appeared proposing Bayesian methods to surmount this limitation. Some of these methods, which require prior knowledge about the quantity, are reviewed in this article.
dc.fuente.origenWOS
dc.identifier.eissn2522-1345
dc.identifier.issn2306-7039
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/92718
dc.identifier.wosidWOS:000971930000001
dc.issue.numero4
dc.language.isoen
dc.pagina.final6
dc.pagina.inicio3
dc.revistaUkrainian metrological journal
dc.rightsacceso restringido
dc.subjectBayesian methods
dc.subjecttype A uncertainty evaluation
dc.subjectprior knowledge
dc.titleAnalysis and comparison of Bayesian methods for type A uncertainty evaluation with prior knowledge
dc.typeartículo
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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