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A new general class of discrete bivariate distributions constructed by using the likelihood ratio

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  • Hyunju Lee

    (Ewha Womans University)

  • Ji Hwan Cha

    (Ewha Womans University)

Abstract

In statistics, stochastic orders formalize such a concept that one random variable is bigger than another. In this paper, we develop a new class of discrete bivariate distributions based on a stochastic order defined by the likelihood ratio. We derive general formula for the joint distributions belonging to the class. It will be seen that, from the proposed class, specific families of distributions can be efficiently generated just by specifying the ‘baseline seed distributions’. An important feature of the proposed discrete bivariate model is that, unlike other discrete bivariate models already proposed in the literature such as the well-known and most popular bivariate Poisson distribution by Holgate, it can model both positive and negative dependence. A number of new families of discrete bivariate distributions are generated from the proposed class. Furthermore, the generated bivariate distributions are applied to analyze real data sets and the results are compared with those obtained from some conventional models.

Suggested Citation

  • Hyunju Lee & Ji Hwan Cha, 2020. "A new general class of discrete bivariate distributions constructed by using the likelihood ratio," Statistical Papers, Springer, vol. 61(3), pages 923-944, June.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:3:d:10.1007_s00362-017-0969-6
    DOI: 10.1007/s00362-017-0969-6
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    References listed on IDEAS

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    Cited by:

    1. Na Young Yoo & Ji Hwan Cha, 2024. "General classes of bivariate distributions for modeling data with common observations," Statistical Papers, Springer, vol. 65(8), pages 5219-5238, October.

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