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Validation of Models: Statistical Techniques and Data Availability
Kleijnen,J.P.C.
Kleijnen,J.P.C.
Abstract
This paper shows which statistical techniques can be used to validate simulation models, depending on which real-life data are available. Concerning this availability three situations are distinguished (i) no data, (ii) only output data, and (iii) both input and output data. In case (i) - no real data - the analysts can still experiment with the simulation model to obtain simulated data; such an experiment should be guided by the statistical theory on the design of experiments. In case (ii) - only output data - real and simulated output data can be compared through the well-known two-sample Student t statistic or certain other statistics. In case (iii) - input and output data - trace-driven simulation becomes possible, but validation should not proceed in the popular way (make a scatter plot with real and simulated outputs, fit a line, and test whether that line has unit slope and passes through the origin); alternative regression and bootstrap procedures are presented. Several case studies are summarized, to illustrate the three types of situations.
Description
Pagination: 9
Date
1999
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Publisher
Operations research
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104.pdf
Adobe PDF, 83.49 KB
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Keywords
Statistical methods, simulation models
Citation
Kleijnen, J P C 1999 'Validation of Models : Statistical Techniques and Data Availability' CentER Discussion Paper, vol. 1999-104, Operations research, Tilburg.