Statistical tools for simulation practitioners
Statistical tools for simulation practitioners
Metamodels for simulation input-output relations
WSC '92 Proceedings of the 24th conference on Winter simulation
Review: Three complementary methods for sensitivity analysis of a water quality model
Environmental Modelling & Software
GAMLSS and neural networks in combat simulation metamodelling: A case study
Expert Systems with Applications: An International Journal
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Simulation metamodels have been used for optimization, prediction, sensitivity analysis and understanding of complex, real-world systems. Since most simulation models contain a large number of input parameters, it is of great interest to determine the most important ones to include in a metamodel given a particular modeling context, i.e. given a particular set of questions which are to be addressed by the metamodel. This paper employs Morris' randomized one-at-a-time (OAT) design as a factor screening method prior to developing a number of simulation metamodels. The approach is illustrated with reference to a stochastic combat simulation, called SIMBAT.