Simulation experiments in practice: statistical design and regression analysis

Simulation experiments in practice: statistical design and regression analysis

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Article ID: iaor20097397
Country: United Kingdom
Volume: 2
Issue: 1
Start Page Number: 19
End Page Number: 27
Publication Date: Mar 2008
Journal: Journal of Simulation
Authors:
Keywords: statistics: experiment
Abstract:

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic DOE and regression analysis assume a single simulation response that is normally and independently distributed with a constant variance; moreover, the regression (meta)model of the simulation model's I/O behaviour is assumed to have residuals with zero means.

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