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Selection of input models using bootstrap goodness-of-fit

Cheng, Russell C.H. and Holland, Wayne S. and Hughes, N.A. (1996) Selection of input models using bootstrap goodness-of-fit. In: Charnes, J.M. and Morrice, D.J. and Brunner, D.T. and Swain, J.J., eds. Proceedings Winter Simulation Conference. IEEE, pp. 199-206. ISBN 0-7803-3383-7. (doi:10.1109/WSC.1996.873279) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:18875)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
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Bootstrap methods are a natural adjunct of computer simulation experiments; both use resampling techniques to construct the statistical distributions of quantities of interest. In this paper we consider how bootstrap methods can be used in selecting appropriate input models for use in a computer simulation experiment. The proposed method uses a goodness-of-fit statistic to decide on which of several competing input models should be used. We use bootstrapping to find the distribution of the test statistic under different assumptions as to which model is the correct fit. This allows the quality of fit of the different models to be compared. The bootstrapping process can be extended to the simulation experiment itself, allowing the effect of variability of estimated parameters on the simulation output to be assessed. The methodology is described and illustrated by application to a queueing example investigating the delays experienced by motorists caused by toll booths at a bridge river crossing.

Item Type: Book section
DOI/Identification number: 10.1109/WSC.1996.873279
Additional information: Amer Stat Assoc; Assoc Comp Machinery, SIGSIM; Inst Operat Res & Management Sci; Inst Operat Res & Management Sci, Coll Simulat; IEEE Comp Soc; IEEE Syst Man & Cybernet Soc; Inst Ind Engineers; NIST; Soc Comp Simulat Int
Uncontrolled keywords: statistical distributions; testing; parameter estimation; statistical analysis; uncertainty; mathematics; computational modeling; computer simulation; delay; bridges
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: M.A. Ziai
Date Deposited: 15 May 2009 10:28 UTC
Last Modified: 16 Nov 2021 09:57 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Cheng, Russell C.H..

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