• DocumentCode
    2615419
  • Title

    A method for fast generation of bivariate poisson random vectors

  • Author

    Shin, Kaeyoung ; Pasupathy, Raghu

  • Author_Institution
    Virginia Tech, Blacksburg
  • fYear
    2007
  • fDate
    9-12 Dec. 2007
  • Firstpage
    472
  • Lastpage
    479
  • Abstract
    It is well known that trivariate reduction - a method to generate two dependent random variables from three independent random variables - can be used to generate Poisson random variables with specified marginal distributions and correlation structure. The method, however, works only for positive correlations. Moreover, the proportion of feasible positive correlations that can be generated through trivariate reduction deteriorates rapidly as the discrepancy between the means of the target marginal distributions increases. We present a specialized algorithm for generating Poisson random vectors, through appropriate modifications to trivariate reduction. The proposed algorithm covers the entire range of feasible correlations in two dimensions, and preliminary tests have demonstrated very fast preprocessing and generation times.
  • Keywords
    Poisson distribution; correlation theory; random processes; vectors; Poisson distribution; bivariate Poisson random vectors; correlation structure; specified marginal distribution; trivariate reduction method; Modeling; Poisson equations; Random variables; Systems engineering and theory; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference, 2007 Winter
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-1306-5
  • Electronic_ISBN
    978-1-4244-1306-5
  • Type

    conf

  • DOI
    10.1109/WSC.2007.4419637
  • Filename
    4419637