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A bivariate geometric distribution allowing for positive or negative correlation

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  • Alessandro Barbiero

Abstract

In this paper, we propose a new bivariate geometric model, derived by linking two univariate geometric distributions through a specific copula function, allowing for positive and negative correlations. Some properties of this joint distribution are presented and discussed, with particular reference to attainable correlations, conditional distributions, reliability concepts, and parameter estimation. A Monte Carlo simulation study empirically evaluates and compares the performance of the proposed estimators in terms of bias and standard error. Finally, in order to demonstrate its usefulness, the model is applied to a real data set.

Suggested Citation

  • Alessandro Barbiero, 2019. "A bivariate geometric distribution allowing for positive or negative correlation," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(11), pages 2842-2861, June.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:11:p:2842-2861
    DOI: 10.1080/03610926.2018.1473428
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