A framework for input uncertainty analysis

Russell R. Barton, Barry L. Nelson, Wei Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations

Abstract

We consider the problem of producing confidence intervals for the mean response of a system represented by a stochastic simulation that is driven by input models that have been estimated from "real-world" data. Therefore, we want the confidence interval to account for both uncertainty about the input models and stochastic noise in the simulation output; standard practice only accounts for the stochastic noise. To achieve this goal we introduce metamodel-assisted bootstrapping, and illustrate its performance relative to other proposals for dealing with input uncertainty on two queueing examples.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 Winter Simulation Conference, WSC'10
Pages1189-1198
Number of pages10
DOIs
StatePublished - 2010
Event2010 43rd Winter Simulation Conference, WSC'10 - Baltimore, MD, United States
Duration: Dec 5 2010Dec 8 2010

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Other

Other2010 43rd Winter Simulation Conference, WSC'10
CountryUnited States
CityBaltimore, MD
Period12/5/1012/8/10

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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