Analysis of simulation factorial experiments by EDF resample statistics
Analysis of simulation factorial experiments by EDF resample statistics
The output from simulation factorial experiments can be complex and may not be amenable to standard methods of estimation like ANOVA. We consider the situation where the simulation output may not satisfy normality assumptions, but more importantly, where there may be differences in output at different factor combinations, but these are not simply differences in means. We show that EDF statistics can provide a similar but potentially more sensitive analysis to that provided by ANOVA. Moreover we show that with the use of resampling, we can generate accurate critical values for tests of hypothesis under much weaker conditions than those required for ANOVA tests. The method is illustrated with an example based on an actual simulation experiment comparing two methods of operating a production facility under different production levels.
0780365798
697-703
Cheng, R.C.H.
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
Jones, O.D.
d5046a34-1cd1-4404-95be-39fa10adc806
2000
Cheng, R.C.H.
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
Jones, O.D.
d5046a34-1cd1-4404-95be-39fa10adc806
Cheng, R.C.H. and Jones, O.D.
(2000)
Analysis of simulation factorial experiments by EDF resample statistics.
Joines, J.A., Barton, R., Fishwick, P.A. and Kang, K.
(eds.)
In Proceedings of the 2000 Winter Simulation Conference.
IEEE.
.
(doi:10.1109/WSC.2000.899782).
Record type:
Conference or Workshop Item
(Paper)
Abstract
The output from simulation factorial experiments can be complex and may not be amenable to standard methods of estimation like ANOVA. We consider the situation where the simulation output may not satisfy normality assumptions, but more importantly, where there may be differences in output at different factor combinations, but these are not simply differences in means. We show that EDF statistics can provide a similar but potentially more sensitive analysis to that provided by ANOVA. Moreover we show that with the use of resampling, we can generate accurate critical values for tests of hypothesis under much weaker conditions than those required for ANOVA tests. The method is illustrated with an example based on an actual simulation experiment comparing two methods of operating a production facility under different production levels.
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Published date: 2000
Venue - Dates:
2000 Winter Simulation Conference, Orlando, FL, USA, 2000-12-10 - 2000-12-13
Organisations:
Operational Research
Identifiers
Local EPrints ID: 29717
URI: http://eprints.soton.ac.uk/id/eprint/29717
ISBN: 0780365798
PURE UUID: 4aa5ab2c-11ef-4e14-8f18-3fd3b2d93be2
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Date deposited: 16 Mar 2007
Last modified: 15 Mar 2024 07:34
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Contributors
Author:
O.D. Jones
Editor:
J.A. Joines
Editor:
R. Barton
Editor:
P.A. Fishwick
Editor:
K. Kang
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