Please use this identifier to cite or link to this item:
Title: On maximum entropy priors and a most likely likelihood in auditing
Authors: Hernández Bastida, Agustín
Martel Escobar, María del Carmen 
Vázquez Polo, Francisco José 
UNESCO Clasification: 530601 Economía, investigación y desarrollo experimental
Keywords: Entropia
Maximum Entropy Prior
Partial Prior Information
Issue Date: 1998
Journal: Questiio 
Abstract: There 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.
ISSN: 0210-8054
Source: Questiió: Quaderns d'Estadística, Sistemes, Informatica i Investigació Operativa [ISSN 0210-8054],v. 22 (2), p. 231-242
Appears in Collections:Artículos
Adobe PDF (77,6 kB)
Show full item record

Page view(s)

checked on Nov 26, 2022


checked on Nov 26, 2022

Google ScholarTM



Export metadata

Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.