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Imprecise Second-Order Hierarchical Uncertainty Model

A hierarchical uncertainty model for combining different evidence is studied in the paper. The model is general enough for many applications. The presented approach for dealing with the model allows us to combine the available heterogeneous information in the following ways: computing new probability bounds for some predefined interval of previsions, computing an "average" interval of first-order previsions, and updating the second-order probabilities after observing new events. Numerical examples illustrate this approach.