• DocumentCode
    2178760
  • Title

    A large deviations view of asymptotic efficiency for simulation estimators

  • Author

    Glynn, Peter W. ; Juneja, Sandeep

  • Author_Institution
    Dept. of Manage. Sci. & Eng., Stanford Univ., Stanford, CA, USA
  • fYear
    2008
  • fDate
    7-10 Dec. 2008
  • Firstpage
    396
  • Lastpage
    406
  • Abstract
    Consider a simulation estimator ¿(c) based on expending c units of computer time, to estimate a quantity ¿. One measure of efficiency is to attempt to minimize P(|¿(c)-¿|>¿) for large c. This helps identify estimators with less likelihood of witnessing large deviations. In this article we establish an exact asymptotic for this probability when the underlying samples are independent and a weaker large deviations result under more general dependencies amongst the underlying samples.
  • Keywords
    convergence; estimation theory; probability; simulation; asymptotic convergence rate; asymptotic efficiency; computer time; probability; simulation estimators; Computational efficiency; Computational modeling; Computer science; Computer simulation; Concrete; Convergence; Distributed computing; Engineering management; Random number generation; Random variables;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference, 2008. WSC 2008. Winter
  • Conference_Location
    Austin, TX
  • Print_ISBN
    978-1-4244-2707-9
  • Electronic_ISBN
    978-1-4244-2708-6
  • Type

    conf

  • DOI
    10.1109/WSC.2008.4736093
  • Filename
    4736093