Analysis of simulation output by resampling
Analysis of simulation output by resampling
Bootstrap resampling is an extremely practical and effective way of studying the distributional properties of simulation output when this is subject to random variation. The purpose of this paper is to show that many problems of sensitivity analysis (SA) and validation can be very simply handled by this method. We consider classical non-parametric version of the bootstrap and show that it can be applied in a natural way in simulation studies without becoming immersed in complicated statistical methodology. The main message of the paper is that the bootstrap method should be the statistical method of first resort in SA and validation studies.
bootstrapping, sensitivity analysis, validation, metamodels
51-58
Cheng, R.C.H.
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
2001
Cheng, R.C.H.
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
Cheng, R.C.H.
(2001)
Analysis of simulation output by resampling.
International Journal of Simulation, 1 (1-2), .
Abstract
Bootstrap resampling is an extremely practical and effective way of studying the distributional properties of simulation output when this is subject to random variation. The purpose of this paper is to show that many problems of sensitivity analysis (SA) and validation can be very simply handled by this method. We consider classical non-parametric version of the bootstrap and show that it can be applied in a natural way in simulation studies without becoming immersed in complicated statistical methodology. The main message of the paper is that the bootstrap method should be the statistical method of first resort in SA and validation studies.
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Published date: 2001
Keywords:
bootstrapping, sensitivity analysis, validation, metamodels
Organisations:
Operational Research
Identifiers
Local EPrints ID: 29720
URI: http://eprints.soton.ac.uk/id/eprint/29720
ISSN: 1473-8031
PURE UUID: 0040da13-c287-40cf-935e-8d96a0f8bcc4
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Date deposited: 12 May 2006
Last modified: 08 Jan 2022 09:56
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