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dc.contributor.authorHernández Bastida, Agustín
dc.contributor.authorMartel Escobar, Mª del Carmen
dc.contributor.authorVázquez Polo, Francisco J.
dc.date.accessioned2007-12-07T12:18:30Z
dc.date.available2007-12-07T12:18:30Z
dc.date.issued1998
dc.identifier.citationHernández Bastida, Agustín; Martel Escobar, Mª del Carmen; Vázquez Polo, Francisco J. "On maximum entropy priors and a most likely likelihood in auditing". Qüestiió. 1998, vol. 22, núm. 2
dc.identifier.issn0210-8054 (versió paper)
dc.identifier.urihttp://hdl.handle.net/2099/4089
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 θ0 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, θ0. We will see some practical applications of the methodology proposed about internal control evaluation in auditing.
dc.format.extent12 p.
dc.language.isoeng
dc.publisherInstitut d'Estadística de Catalunya
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/es/
dc.subject.lcshStatistics
dc.subject.lcshDecision theory
dc.subject.otherMaximum entropy
dc.subject.otherPartial prior information
dc.subject.otherAuditing
dc.titleOn maximum entropy priors and a most likely likelihood in auditing
dc.typeArticle
dc.subject.lemacEstadística
dc.subject.lemacTeoria de la decisió
dc.subject.amsClassificació AMS::62 Statistics::62A01 Foundational and philosophical topics
dc.subject.amsClassificació AMS::62 Statistics::62C Decision theory
dc.rights.accessOpen Access


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 2.5 Spain