Sharp polynomial upper bound on the variance
De Angelis, Marco; Ansari, Jonathan and Fuchs, Sebastian and Trutschnig, Wolfgang and Asunción Lubiano, María and Gil, María Ángeles and Grzegorzewski, Przemyslaw and Hryniewicz, Olgierd, eds. (2024) Sharp polynomial upper bound on the variance. In: Combining, Modelling and Analyzing Imprecision, Randomness and Dependence. Advances in Intelligent Systems and Computing . Springer, AUT, pp. 76-84. ISBN 9783031659935 (https://doi.org/10.1007/978-3-031-65993-5_9)
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Abstract
This short paper presents a new idea leading to a very sharp upper bound on the variance of interval-valued data. The computation of this sharp bound can be carried out in polynomial time in the worst case. For a whole class of interval data this bound is exact as it can be shown that it coincides with the maximum. The algorithm derives from posing the optimisation problem in probabilistic terms, i.e. thinking beyond the deterministic interpretation of an interval. Interval-valued variance can be seen from an imprecise probability’s perspective. There are two alternative and non-competing connotations of an interval: a set of real values, and a credal set of all possible probability measures in the given interval. These two connotations do not precipitate any quantitative discrepancies for interval arithmetic. In fact, interval arithmetic provides a means to compute with these imprecise probabilistic objects. This work demonstrates the computational advantage that originates from looking at intervals from an imprecise probabilistic angle, and it may serve as a testimony towards filling the computational void that has for too long discouraged practitioners from computing with interval statistics.
ORCID iDs
De Angelis, Marco ORCID: https://orcid.org/0000-0001-8851-023X; Ansari, Jonathan, Fuchs, Sebastian, Trutschnig, Wolfgang, Asunción Lubiano, María, Gil, María Ángeles, Grzegorzewski, Przemyslaw and Hryniewicz, Olgierd-
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Item type: Book Section ID code: 89792 Dates: DateEvent10 August 2024Published30 April 2024AcceptedSubjects: Science > Mathematics > Probabilities. Mathematical statistics Department: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 01 Jul 2024 14:48 Last modified: 01 Oct 2024 14:59 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/89792