Single-experiment input uncertainty

Abstract

‘Input uncertainty’ refers to the simulation model risk caused by estimating input distributions from real-world data, and specifically the (usually unmeasured) variance in performance estimates that this introduces. We provide the first single-run method for quantifying input uncertainty, meaning that we derive our measure of input-uncertainty variance—both overall variance and the contribution to it of each input model—from the nominal experiment that the analyst would typically run using the estimated input models; other methods in the literature require additional diagnostic experiments. Application of our method is illustrated with two examples. Journal of Simulation (2015) 9(3), 249–259. doi:10.1057/jos.2015.2; published online 27 February 2015

DOI: 10.1057/jos.2015.2

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Cite this paper

@article{Lin2015SingleexperimentIU, title={Single-experiment input uncertainty}, author={Y. Lin and Eunhye Song and Barry L. Nelson}, journal={J. Simulation}, year={2015}, volume={9}, pages={249-259} }