A bivariate geometric distribution allowing for positive or negative correlation. Issue 11 (3rd June 2019)

• Record Type: Journal Article
• Authors: Barbiero, Alessandro
• Is Part Of: Communications in statistics. Volume 48:Issue 11(2019)
• Page Start: 2842
• Page End: 2861
• Publication Date: 2019-06-03
• Subjects: Attainable correlations -- correlated counts -- Farlie-Gumbel-Morgenstern copula -- method of moments -- two-step maximum likelihood; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2018.1473428
• Languages: English
• ISSNs: 0361-0926

Abstract

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.