A mixture of Clayton, Gumbel, and Frank copulas: a complete dependence model

DOI10.1155/2022/1422394OpenAlexW4224019147MaRDI QIDQ2149175

Maxwell Akwasi Boateng, Richard Kodzo Avuglah, Nana Kena Frempong, Akoto Yaw Omari-Sasu

Publication date: 28 June 2022

Published in: Journal of Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2022/1422394

Mathematics Subject Classification ID

Multivariate analysis (62Hxx) Nonparametric inference (62Gxx) Functional equations and inequalities (39Bxx)

Cites Work

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• On the simultaneous associativity of F(x,y) and x+y-F(x,y)
• Hybrid Clayton-Frank convolution-based bivariate Archimedean copula
• Tests of symmetry for bivariate copulas
• Vine copulas with asymmetric tail dependence and applications to financial return data
• Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins
• Problems on associative functions
• Bivariate Exponential Distributions
• Empirical estimation of tail dependence using copulas: application to Asian markets
• A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
• Do stock returns have an Archimedean copula?
• Understanding Relationships Using Copulas
• Statistics of financial markets. An introduction.

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