On the Use of Random Set Theory to Bracket the Results of Monte Carlo Simulations

On the Use of Random Set Theory to Bracket the Results of Monte Carlo Simulations Based on Random Set Theory, procedures are presented for bracketing the results of Monte Carlo simulations in two notable cases: (i) the calculation of the entire distribution of the dependent variable; (ii) the calculation of the CDF of a particular value of the dependent variable (e.g. reliability analyses). The presented procedures are not intrusive in that they can be equally applied when the functional relationship between the dependent variable and independent variables is known analytically and when it is a complex computer model (black box). Also, the proposed procedures can handle probabilistic (with any type of input joint PDF), interval-valued, set-valued, and random set-valued input information, as well as any combination thereof. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Reliable Computing Springer Journals

On the Use of Random Set Theory to Bracket the Results of Monte Carlo Simulations

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Publisher
Springer Journals
Copyright
Copyright © 2004 by Kluwer Academic Publishers
Subject
Mathematics; Numeric Computing; Approximations and Expansions; Computational Mathematics and Numerical Analysis; Mathematical Modeling and Industrial Mathematics
ISSN
1385-3139
eISSN
1573-1340
D.O.I.
10.1023/B:REOM.0000015849.35108.9c
Publisher site
See Article on Publisher Site

Abstract

Based on Random Set Theory, procedures are presented for bracketing the results of Monte Carlo simulations in two notable cases: (i) the calculation of the entire distribution of the dependent variable; (ii) the calculation of the CDF of a particular value of the dependent variable (e.g. reliability analyses). The presented procedures are not intrusive in that they can be equally applied when the functional relationship between the dependent variable and independent variables is known analytically and when it is a complex computer model (black box). Also, the proposed procedures can handle probabilistic (with any type of input joint PDF), interval-valued, set-valued, and random set-valued input information, as well as any combination thereof.

Journal

Reliable ComputingSpringer Journals

Published: Oct 18, 2004

References

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