Transforming probability intervals into other uncertainty models

Abstract : Probability intervals are imprecise probability assignments over elementary events. They constitute a very convenient tool to model uncertain information : two common cases are confidence intervals on parameters of multinomial distributions built from sample data and expert opinions provided in terms of such intervals. In this paper, we study how probability intervals can be transformed into other uncertainty models such as possibility distributions, Ferson's p-boxes, random sets and Neumaier's clouds.