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Identifying the important factors in simulation models with many factors

Author

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  • Bettonvil, B.
  • Kleijnen, J.P.C.

    (Tilburg University, Center For Economic Research)

Abstract

Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The technique extends the classical binary search technique to situations with more than a single important factor. The technique uses a low-order polynomial approximation to the input/output behavior of the simulation model. This approximation may account for interactions among factors. The technique is demonstrated by applying it to a complicated ecological simulation that models the increase of temperatures worldwide.
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Suggested Citation

  • Bettonvil, B. & Kleijnen, J.P.C., 1994. "Identifying the important factors in simulation models with many factors," Discussion Paper 1994-114, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:5da4bf9f-3126-4cf9-954f-f2140dbd8b4c
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    File URL: https://pure.uvt.nl/ws/portalfiles/portal/520060/114.pdf
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    References listed on IDEAS

    as
    1. Jack P. C. Kleijnen & Ben Annink, 1992. "Vector Computers, Monte Carlo Simulation and Regression Analysis: An Introduction," Management Science, INFORMS, vol. 38(2), pages 170-181, February.
    2. van Groenendaal, W.J.H., 1994. "Investment analysis and decision support for gas transmission on Java," Other publications TiSEM ada5b6e7-0462-411e-9a8c-1, Tilburg University, School of Economics and Management.
    3. J. E. Jacoby & S. Harrison, 1962. "Multi‐variable experimentation and simulation models," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(2), pages 121-136, June.
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    Citations

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    Cited by:

    1. Kleijnen, Jack P.C., 1992. "Sensitivity analysis of simulation experiments: regression analysis and statistical design," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 34(3), pages 297-315.
    2. Kleijnen, J.P.C., 1995. "Statistical validation of simulation models : A case study," Discussion Paper 1995-42, Tilburg University, Center for Economic Research.
    3. Kleijnen, J.P.C. & Alink, G.A., 1992. "Validation of simulation models : Mine-hunting case-study," Other publications TiSEM 7158fbd4-2932-4cc9-8c10-5, Tilburg University, School of Economics and Management.
    4. Kleijnen, Jack P. C., 1995. "Statistical validation of simulation models," European Journal of Operational Research, Elsevier, vol. 87(1), pages 21-34, November.
    5. Kleijnen, Jack P. C., 1995. "Verification and validation of simulation models," European Journal of Operational Research, Elsevier, vol. 82(1), pages 145-162, April.
    6. Kleijnen, J.P.C., 1995. "Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments," Other publications TiSEM 87ee6ee0-592c-4204-ac50-6, Tilburg University, School of Economics and Management.

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    1. Kleijnen, J.P.C., 1995. "Sensitivity analysis and related analysis : A survey of statistical techniques," Research Memorandum FEW 706, Tilburg University, School of Economics and Management.
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    Keywords

    Simulation Models; econometrics;

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