Joint criterion for factor identification and parameter estimation

One goal in simulation experimentation is to identify which input parameters most significantly influence the mean of simulation output. Another goal is to obtain good parameter estimates for a response model that quantifies how the mean output depends on influential input parameters. The majority of experimental design techniques focus on either one goal or the other. This paper uses a design criterion for follow-up experiments that jointly identifies the important parameters and reduces the variance of parameter estimates. The criterion is entropy-based; and is applied to a critical care facility simulation.

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