The Comparison of Approaches Used for Estimating Uncertain Probabilities

Oleg Uzhga-Rebrov, Galina Kuleshova


Probabilistic estimates are numerical representations of chances of random event occurrence. The classical theory of probability is based on the assumption that probabilistic estimates are deterministic. If available initial data are sufficient, this kind of estimates can be really obtained. However, when such data are not available, probabilistic estimates become uncertain. This paper analyses and compares three widespread approaches to modelling uncertain estimates and provides practical recommendations on their use.


Choquet capacities; interval probabilities; lower and upper probabilities; -measures; monotone measures; Möbius representation

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