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Experimental design for sensitivity analysis of simulation models

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Author Info
Kleijnen, J.P.C. (Tilburg University, Center for Economic Research)

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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 ... 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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Publisher Info
Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 15.

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Date of creation: 2001
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Handle: RePEc:dgr:kubcen:200115

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Web page: http://center.uvt.nl

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  1. Kleijnen, J.P.C., 1997. "Experimental design for sensitivity analysis, optimization, and validation of simulation models," Discussion Paper 52, Tilburg University, Center for Economic Research. [Downloadable!]
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