Validation of trace-driven simulation models: bootstrap tests
Validation of trace-driven simulation models: bootstrap tests
Trace-driven (or correlated inspection) simulation means that the simulated and the real systems have some common inputs (say, historical arrival times) so that the two systems' outputs are cross-correlated. To validate such a simulation, this paper focuses on the difference between the average simulated and real responses. To evaluate this validation statistic, the paper develops a novel bootstrap technique--based on replicated runs. This validation statistic and the bootstrap technique are evaluated in extensive Monte Carlo experiments with specific single-server queues. These experiments show acceptable Type-I and Type-II error probabilities.
time series, dependence, paired observations, error rates, power
1533-1538
Kleijnen, Jack P.C.
ccf6daf6-ea64-4800-ab07-9565bf6839b3
Cheng, Russell C.H.
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
Bettonvil, Bert
03c94bfd-3aa5-4f5e-9a27-a9920fc981dc
2001
Kleijnen, Jack P.C.
ccf6daf6-ea64-4800-ab07-9565bf6839b3
Cheng, Russell C.H.
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
Bettonvil, Bert
03c94bfd-3aa5-4f5e-9a27-a9920fc981dc
Kleijnen, Jack P.C., Cheng, Russell C.H. and Bettonvil, Bert
(2001)
Validation of trace-driven simulation models: bootstrap tests.
Management Science, 47 (11), .
(doi:10.1287/mnsc.47.11.1533.10255).
Abstract
Trace-driven (or correlated inspection) simulation means that the simulated and the real systems have some common inputs (say, historical arrival times) so that the two systems' outputs are cross-correlated. To validate such a simulation, this paper focuses on the difference between the average simulated and real responses. To evaluate this validation statistic, the paper develops a novel bootstrap technique--based on replicated runs. This validation statistic and the bootstrap technique are evaluated in extensive Monte Carlo experiments with specific single-server queues. These experiments show acceptable Type-I and Type-II error probabilities.
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Published date: 2001
Keywords:
time series, dependence, paired observations, error rates, power
Organisations:
Operational Research
Identifiers
Local EPrints ID: 29721
URI: http://eprints.soton.ac.uk/id/eprint/29721
ISSN: 0025-1909
PURE UUID: f87ebf6f-350f-4721-85e8-fcc2a73ef833
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Date deposited: 11 May 2006
Last modified: 15 Mar 2024 07:34
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Contributors
Author:
Jack P.C. Kleijnen
Author:
Russell C.H. Cheng
Author:
Bert Bettonvil
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