A methodology for fitting and validating metamodels in simulation

1 Introduction Simulation-based analysis tools are finding increased use during preliminary design to explore desi...

Citation Context ..kriging method has advantages in that it provides a basis for a stepwise algorithm to determine the important factors, and the same data can be used for screening and building the predictor model (=-=Welch, et al., 1992)-=-.

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TY - UNPBT1 - A Methodology for Fitting and Validating Metamodels in Simulation AU - Kleijnen, J. There are several types of metamodel: linear regression, splines, neural networks, etc.

Illustrations of our model are given for both synthetic and real datasets.

Classic design of experiments (DOE) is summarized, including standard measures of fit such as the R-square coefficient and cross-validation measures.

This DOE is extended to sequential or stagewise DOE.

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