Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/71018
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dc.contributor.authorHernández Bastida, Agustínen_US
dc.contributor.authorMartel Escobar, María del Carmenen_US
dc.contributor.authorVázquez Polo, Francisco Joséen_US
dc.date.accessioned2020-03-23T16:59:23Z-
dc.date.available2020-03-23T16:59:23Z-
dc.date.issued1998en_US
dc.identifier.issn0210-8054en_US
dc.identifier.otherDialnet-
dc.identifier.urihttp://hdl.handle.net/10553/71018-
dc.description.abstractThere are two basic questions auditors and accountants must consider when developing test and estimation applications using Bayes' Theorem: What prior probability function should be used and what likelihood function should be used. In this paper we propose to use a maximum entropy prior probability function MEP with the most likely likelihood function MLL in the Quasi-Bayesian QB model introduced by McCray (1984). It is defined on an adequate parameter. Thus procedure only needs an expected value of ?0 known (in this paper the expected tainting) to obtain a MEP all an auditor or accountant need to supply are the range, as with any other prior, and the expected tainting, ?0. We will see some practical applications of the methodology proposed about internal control evaluation in auditin.en_US
dc.languageengen_US
dc.relation.ispartofQuestiioen_US
dc.sourceQuestiió: Quaderns d'Estadística, Sistemes, Informatica i Investigació Operativa [ISSN 0210-8054],v. 22 (2), p. 231-242en_US
dc.subject530601 Economía, investigación y desarrollo experimentalen_US
dc.subject.otherEntropiaen_US
dc.subject.otherAuditoríaen_US
dc.subject.otherAuditingen_US
dc.subject.otherMaximum Entropy Prioren_US
dc.subject.otherPartial Prior Informationen_US
dc.titleOn maximum entropy priors and a most likely likelihood in auditingen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.urlhttp://dialnet.unirioja.es/servlet/articulo?codigo=2363828-
dc.description.lastpage242-
dc.identifier.issue2-
dc.description.firstpage231-
dc.relation.volume22-
dc.investigacionCiencias Sociales y Jurídicasen_US
dc.type2Artículoen_US
dc.contributor.authordialnetidNo ID-
dc.contributor.authordialnetid1132051-
dc.contributor.authordialnetid243388-
dc.identifier.dialnet2363828ARTREV-
dc.utils.revisionen_US
dc.identifier.ulpgces
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.author.deptGIR Técnicas estadísticas bayesianas y de decisión en la economía y empresa-
crisitem.author.deptIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.deptGIR Técnicas estadísticas bayesianas y de decisión en la economía y empresa-
crisitem.author.deptIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.orcid0000-0002-7013-4747-
crisitem.author.orcid0000-0002-0632-6138-
crisitem.author.parentorgIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.parentorgIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.fullNameMartel Escobar, María Carmen-
crisitem.author.fullNameVázquez Polo, Francisco José-
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