A Comparison of Methods for Transforming Belief Function Models to Probability Models

This 12-pp paper is extracted from a longer unpublished working paper: "On Transforming Belief Function Models to Probability Models," School of Business Working Paper No. 293, July 2003, University of Kansas, Lawrence, KS.Recently, we proposed a new method called the plausibility transformation method to convert a belief function model to an equivalent probability model. In this paper, we compare the plausibility transformation method with the pignistic transformation method. The two transformation methods yield qualitatively di®erent probability models. We argue that the plausibility transformation method is the correct method for translating a belief function model to an equivalent probability model that maintains belief function semantics