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Please use this identifier to cite or link to this item: http://hdl.handle.net/1808/156
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dc.contributor.authorCobb, Barry R.-
dc.contributor.authorShenoy, Prakash P.-
dc.date.accessioned2004-12-15T17:06:57Z-
dc.date.available2004-12-15T17:06:57Z-
dc.date.issued2003-07-
dc.identifier.citationCobb, B. R. and P. P. Shenoy (2003), "On Transforming Belief Function Models to Probability Models," University of Kansas School of Business Working Paper No. 293, July 2003, Revised February 2004, Lawrence, KS.en
dc.identifier.urihttp://hdl.handle.net/1808/156-
dc.descriptionIn response to reviewer comments on this paper, we have written a shorter and more focused paper: "On the Plausibility Transformation Method for Translating Belief Function Models to Probability Models," University of Kansas School of Business Working Paper No. 308, June 2004, Lawrence, KS.en
dc.description.abstractIn this paper, we explore methods for transforming a belief function model to an equivalent probability model. We propose and define the properties of a method called the plausibility transformation method. We compare the plausibility transformation method with the pignistic transformation method. These two methods yield qualitatively different probability models. We argue that the plausibility transformation method is the correct method that maintains belief function semantics.en
dc.format.extent1475219 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen_US-
dc.publisherUniversity of Kansas School of Businessen
dc.relation.ispartofseriesSchool of Business Working Paper;No. 293-
dc.subjectDempster-Shafer belief functionsen
dc.subjectPlausibility transformation methoden
dc.subjectPignistic transformation methoden
dc.subjectTransforming belief function models to probability modelsen
dc.subjectBayesian networksen
dc.subjectvaluation networksen
dc.subjectvaluation-based systemsen
dc.titleOn Transforming Belief Function Models to Probability Modelsen
dc.typeWorking Paperen
Appears in Collections:School of Business Working Papers

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