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Activity Number: 411 - Copula Model and Maximum Likelihood Estimation
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 2:00 PM to 3:50 PM
Sponsor: Business and Economic Statistics Section
Abstract #327051 Presentation
Title: Modeling Count Data via Copulas: Comparison of Kendall's Tau and Spearman's Rho
Author(s): Hadi Safari Katesari* and Samira Zaroudi and Reza Safari Katesari and S. Yaser Samadi
Companies: Southern Illinois ?University, Carbondale and Science and Research Branch, Islamic Azad University and Payame Noor University and Southern Illinois University
Keywords: Copula; Spearman's Rho; count data

Copula models have been widely used to model dependence between con- tinuous random variables, but modelling count data via copulas has recently become popular in the statistics literature. Spearman's rho is a widely used measure for the strength of association between two random variables. In this talk, we propose the population version of Spearman's rho correlation via copulas when both random variables are discrete. The explicit form of the Spearman correlation are obtained for some copulas of simple structure such as Archimedean copula family. Then, the Spearman's rho correlations are compared with their corresponding Kendall's tau values. Finally, the results are applied to model the count data in our simulation study and a real data analysis.

Authors who are presenting talks have a * after their name.

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