Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4949622 | Discrete Applied Mathematics | 2017 | 20 Pages |
Abstract
The contribution of the shape information of the underlying distribution in probability bounding problem is investigated and a linear programming based bounding methodology to obtain robust and efficiently computable bounds for the probability that at least k-out-of-n events occur is developed. The dual feasible basis structures of the relaxed versions of linear programs involved are fully described. The bounds for the probability that at least k-out-of-n events occur are obtained in the form of formulas and as the customized algorithmic solutions of the LP's formulated. An application in finance is presented.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Munevver M. Subasi, Ersoy Subasi, Ahmed Binmahfoudh, András Prékopa,