Experimental Designs for Sensitivity Analysis of Simulation Models

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. This regression analysis gives better results when the simulation experiment is well designed, using classical statistical designs (such as fractional factorials, including 2 designs). These statistical techniques reduce the ad hoc character of k p simulation; that is, these techniques can make simulation studies give more general results, in less time.