We are pleased to announce that our paper
On the closedness of imprecise probability models under aggregation
has been accepted for publication in the International Journal of General Systems.
This paper, authored by Enrique Miranda and Ignacio Montes, explores the aggregation of particular families of imprecise probability models, and continues our line of research on the aggregation of imprecise probability models, initiated with our previous publication “A Comparative Analysis of Aggregation Rules for Coherent Lower Previsions” and the conference paper “On the commutativity of the aggregation of coherent lower probabilities and the natural extension to gambles”.
In particular, in this contribution we consider six different models, namely comparative probabilities (Section 4), 2-monotone capacities (Section 5), probability intervals (Section 6), belief functions (Section 7), minitive measures (Section 8), and p-boxes (Section 9). For each of these models, we analyse whether several aggregation rules (conjunction, disjunction, convex mixtures, Pareto, conjunction–disjunction, and maximal consistent subsets rules) are closed within the family, in the sense that if the initial models to be aggregated belong to one of these families, the resulting model also belongs to the same family.