• DocumentCode
    2776599
  • Title

    Input modeling when simple models fail

  • Author

    Nelson, Barry L. ; Ware, Peter ; Cario, Marne C. ; Harris, Chester A. ; Jamison, Stephanie A. ; Miller, J.O. ; Steinbugl, James ; Yang, Jaehwan

  • Author_Institution
    Dept. of Ind. Eng. & Manage. Sci., Northwestern Univ., Evanston, IL, USA
  • fYear
    1995
  • fDate
    3-6 Dec 1995
  • Firstpage
    93
  • Lastpage
    100
  • Abstract
    A simulation model is composed of inputs and logic; the inputs represent the uncertainty or randomness in the system, while the logic determines how the system reacts to the uncertain elements. Simple input models, consisting of independent and identically distributed sequences of random variates from standard probability distributions, are included in every commercial simulation language. Software to fit these distributions to data is also available. In this tutorial we describe input models that are useful when simple models are not
  • Keywords
    digital simulation; probability; simulation languages; input modeling; logic; probability distributions; randomness; simple models; simulation language; simulation model; uncertainty; univariate input models; Computational modeling; Information science; Inspection; Integrated circuit modeling; Logic; Probability distribution; Random variables; Testing; Uncertainty; Welding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference Proceedings, 1995. Winter
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    0-78033018-8
  • Type

    conf

  • DOI
    10.1109/WSC.1995.478710
  • Filename
    478710