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
Link To Document :
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