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Nikoloulopoulos, Aristidis K 
ORCID: https://orcid.org/0000-0003-0853-0084 and Karlis, Dimitris
(2009)
Finite normal mixture copulas for multivariate discrete data modeling.
Journal of Statistical Planning and Inference, 139 (11).
pp. 3878-3890.
Abstract
A new family of copulas is introduced that provides flexible dependence structure while being tractable and simple to use for multivariate discrete data modeling. The construction exploits finite mixtures of uncorrelated normal distributions. Accordingly, the cumulative distribution function is simply the product of univariate normal distributions. At the same time, however, the mixing operation introduces association. The properties of the new family of copulas are examined and a concrete application is used to show its applicability.
| 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 16:30 |
| Last Modified: | 07 Nov 2024 12:33 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/22925 |
| DOI: | 10.1016/j.jspi.2009.05.034 |
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