Abstract
In practice, simulation models usually have a great many parameters and input variables. This paper presents a screening technique which identifies the really important factors. The technique treats the simulation model as a black box and uses a regression metamodel to approximate the input/output behaviour of that black box. The metamodel can account for fitting errors with unknown variance and for interactions among factors. The technique requires relatively few simulation runs and applies to both random and deterministic simulations. The technique is demon strated through a case study of a complicated ecological model.
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