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Experimental designs for sensitivity analysis of simulation models

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  • Kleijnen, J.P.C.

    (Tilburg University)

Abstract

This introductory tutorial gives a survey on the use of statistical designs for what if-or sensitivity analysis in simulation.This analysis uses regression analysis to approximate the input/output transformation that is implied by the simulation model; the resulting regression model is also known as metamodel, response surface, compact model, emulator, etc.Regression analysis gives better results when the simulation experiment is well designed, using classical statistical designs (such as fractional factorials, including 2 k-p designs).These statistical techniques reduce the ad hoc character of simulation; that is, these techniques can make simulation studies give more general results, in less time.

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Bibliographic Info

Paper provided by Tilburg University in its series Open Access publications from Tilburg University with number urn:nbn:nl:ui:12-86474.

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Date of creation: 2001
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Handle: RePEc:ner:tilbur:urn:nbn:nl:ui:12-86474

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Web page: http://www.tilburguniversity.edu/

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  1. Jack P. C. Kleijnen, 1992. "Regression Metamodels for Simulation with Common Random Numbers: Comparison of Validation Tests and Confidence Intervals," Management Science, INFORMS, INFORMS, vol. 38(8), pages 1164-1185, August.
  2. Kleijnen, J.P.C., 1993. "Simulation and optimization in production planning: a case study," Open Access publications from Tilburg University, Tilburg University urn:nbn:nl:ui:12-369798, Tilburg University.
  3. Kleijnen, J.P.C. & Groenendaal, W.J.H. van, 1992. "Simulation: A statistical perspective," Open Access publications from Tilburg University, Tilburg University urn:nbn:nl:ui:12-388278, Tilburg University.
  4. Kleijnen, J.P.C., 1997. "Experimental Design for Sensitivity Analysis, Optimization and Validation of Simulation Models," Discussion Paper, Tilburg University, Center for Economic Research 1997-52, Tilburg University, Center for Economic Research.
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