The bivariate K-finite normal mixture 'blanket' copula

Nikoloulopoulos, Aristidis K. ORCID: (2022) The bivariate K-finite normal mixture 'blanket' copula. Journal of Statistical Computation and Simulation, 92 (6). pp. 1224-1245. ISSN 0094-9655

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There exist many bivariate parametric copulas to model bivariate data with different dependence features. We propose a new bivariate parametric copula family that cannot only handle various dependence patterns that appear in the existing parametric bivariate copula families, but also provides a more enriched dependence structure. The proposed copula construction exploits finite mixtures of bivariate normal distributions. The mixing operation, the distinct correlation and mean parameters at each mixture component introduce quite a flexible dependence. The new parametric copula is theoretically investigated, compared with a set of classical bivariate parametric copulas and illustrated on two empirical examples from astrophysics and agriculture where some of the variables have peculiar and asymmetric dependence, respectively.

Item Type: Article
Uncontrolled Keywords: bivariate copulas,kullback–leibler distance,dependence structure,mixtures of bivariate normal distributions,statistics and probability,modelling and simulation,statistics, probability and uncertainty,applied mathematics,3* ,/dk/atira/pure/subjectarea/asjc/2600/2613
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Data Science and Statistics
Faculty of Science > Research Groups > Statistics
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Depositing User: LivePure Connector
Date Deposited: 06 Oct 2021 01:59
Last Modified: 05 Dec 2023 02:11
DOI: 10.1080/00949655.2021.1990292


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