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Abstract Details
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Activity Number:
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583
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #301097 |
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Title:
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Introducing a Generalized Bivariate Distribution for Count Data
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Author(s):
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Kimberly F. Sellers*+ and Narayanaswamy Balakrishnan
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Companies:
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Georgetown University and McMaster University
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Address:
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306 St. Mary's Hall, Washington, DC, 20057,
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Keywords:
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bivariate Poisson distribution ;
bivariate geometric distribution ;
bivariate Bernoulli distribution ;
Conway-Maxwell-Poisson ;
dispersion
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Abstract:
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The bivariate Poisson distribution is a popular distribution for modeling bivariate count data. Its associated assumptions, however, may prove limiting in some contexts. To allow for data dispersion, we develop a bivariate Conway-Maxwell-Poisson (COM-Poisson) distribution that includes the bivariate Poisson, bivariate geometric, and bivariate Bernoulli distributions as special cases. As a result, the bivariate COM-Poisson distribution serves as a flexible alternative for modeling bivariate count data, particularly in the presence of data dispersion.
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