Article ID Journal Published Year Pages File Type
395990 Information Sciences 2007 12 Pages PDF
Abstract

The results in this paper are about the convergence of capacity functionals of random sets. The motivation stems from asymptotic aspects in inference and decision-making with coarse data in biostatistics, set-valued observations, as well as connections between random sets with several emerging uncertainty calculi in intelligent systems such as fuzziness, belief functions and possibility theory. Specifically, we study the counter-part of Billingsley’s Portmanteau Theorem for weak convergence of probability measures, namely, convergence of capacity functionals of random sets in terms of Choquet integrals.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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