Regression in a copula model for bivariate count data

Nikoloulopoulos, Aristidis K. ORCID: https://orcid.org/0000-0003-0853-0084 and Karlis, Dimitris (2010) Regression in a copula model for bivariate count data. Journal of Applied Statistics, 37 (9). pp. 1555-1568. ISSN 1360-0532

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Abstract

In many cases of modeling bivariate count data, the interest lies on studying the association rather than the marginal properties. We form a flexible regression copula-based model where covariates are used not only for the marginal but also for the copula parameters. Since copula measures the association, the use of covariates in its parameters allow for direct modeling of association. A real-data application related to transaction market basket data is used. Our goal is to refine and understand whether the association between the number of purchases of certain product categories depends on particular demographic customers’ characteristics. Such information is important for decision making for marketing purposes.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Data Science and AI
Faculty of Science > Research Groups > Statistics (former - to 2024)
Faculty of Science > Research Groups > Numerical Simulation, Statistics & Data Science
Depositing User: Vishal Gautam
Date Deposited: 11 Mar 2011 16:31
Last Modified: 07 Nov 2024 12:33
URI: https://ueaeprints.uea.ac.uk/id/eprint/22920
DOI: 10.1080/02664760903093591

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