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Integrating statistical audit evidence with belief function theory. (English) Zbl 1419.68136

Gabbay, Dov M. (ed.) et al., Practical reasoning. International conference on formal and applied practical reasoning, FAPR ’96, Bonn, Germany, June 3–7, 1996. Proceedings. Berlin: Springer. Lect. Notes Comput. Sci. 1085, 1-14 (1996).
Summary: This paper proposes a method for integrating statistical audit evidence (sampling evidence) with belief function theory. Our point of view is the interpretation of belief-function theory as a theory of evidence. The need for integration is urged by the suitability of belief function theory to model the auditor’s thought process of collecting and aggregating evidence on the one hand, and the frequent use of both statistical and non-statistical evidence in auditing practice on the other hand. The method we propose is of a general nature and is motivated by the analogy with the way in which sampling evidence is used in auditing practice. Its properties are briefly discussed from the point view of probability theory, though the main part of the paper concentrates on our proposed method and a comparison with G. Shafer’s [A mathematical theory of evidence. Princeton, London: Princeton University Press (1976; Zbl 0359.62002)]. Several examples are used to demonstrate both methods’ properties.
For the entire collection see [Zbl 0937.00049].

MSC:

68T27 Logic in artificial intelligence
62A01 Foundations and philosophical topics in statistics
68T37 Reasoning under uncertainty in the context of artificial intelligence

Citations:

Zbl 0359.62002
Full Text: DOI

References:

[1] Dempster, A.P. 1990. Construction and local computation aspects of network belief functions, in: Oliver, R.M. ea. Influence Diagrams, Belief Nets, and Decision Analysis, Wiley, N.Y.
[2] Fisher, R.A., 1950. Contributions to Mathematical Statistics, Wiley, N.Y. · Zbl 0040.36201
[3] Hacking, I., 1965. Logic of Statistical Inference, Cambridge University Press, U.K. · Zbl 0133.41604
[4] Halpern, J., Fagin, R. 1992. Two views of belief: belief as generalized probability and belief as evidence. Artificial Intelligence, vol. 54, p. 275-317. · Zbl 0762.68055 · doi:10.1016/0004-3702(92)90048-3
[5] Shafer, G. 1976. A Mathematical Theory of Evidence, Princeton University Press. · Zbl 0359.62002
[6] Shafer, G. 1990. Perspectives on the Theory and Practice of Belief Functions, International Journal of Approximate Reasoning, vol 4, p. 323-362. · Zbl 0714.62001 · doi:10.1016/0888-613X(90)90012-Q
[7] Shafer, G., Srivastava, R. 1990. The Bayesian and Belief-Function Formalisms: A General Perspective for Auditing, Auditing: A Journal of Practice & Theory, vol 9 (suppl.), p. 110-148
[8] Smets, P. 1994. Belief Induced by the Knowledge of the Probabilities. Technical Report IRIDIA no. 94-4.1, 8p.
[9] Srivastava, R. and Shafer, G. 1994. Integrating Statistical and Nonstatistical Audit Evidence Using Belief Functions: A Case of Variable Sampling. · Zbl 0801.62100
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