• DocumentCode
    1740939
  • Title

    How the ExpertFit distribution-fitting package can make your simulation models more valid

  • Author

    Law, Averill M. ; McComas, Michael G.

  • Author_Institution
    Averill M. Law & Assoc. Inc., Tucson, AZ, USA
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    253
  • Abstract
    In this paper, we discuss the critical role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we explain how any analyst, regardless of their knowledge of statistics, can easily avoid these pitfalls through the use of the ExpertFit distribution-fitting software. We use a set of real-world data to demonstrate how the software automatically specifies and ranks probability distributions, and then tells the analyst whether the “best” candidate distribution is actually a good representation of the data. If no distribution provides a good fit, then ExpertFit can define an empirical distribution. In either case, the selected distribution is put into the proper format for direct input to the analyst´s simulation software
  • Keywords
    digital simulation; manufacturing resources planning; statistical analysis; ExpertFit distribution-fitting package; ranks probability; real-world data; simulation input modeling; simulation models; simulation software; simulation study; Analytical models; Fitting; Information analysis; Machine tools; Manufacturing systems; Packaging; Probability distribution; Statistical analysis; Statistical distributions; World Wide Web;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference, 2000. Proceedings. Winter
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-6579-8
  • Type

    conf

  • DOI
    10.1109/WSC.2000.899726
  • Filename
    899726