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On the Construction of Radially Symmetric Trivariate Copulas

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Soft Methods for Data Science (SMPS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 456))

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Abstract

We propose a method to construct a 3-dimensional symmetric function that is radially symmetric, using two symmetric 2-copulas, with one of them being also radially symmetric. We study the properties of the presented construction in some specific cases and provide several examples for different families of copulas.

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Acknowledgments

The first author was supported by the “Consejo Nacional de Ciencia y Tecnología" (México) grant number 382963.

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Authors and Affiliations

  1. KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure links 653, 9000, Ghent, Belgium

    José De Jesús Arias García & Bernard De Baets

  2. Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281 S9, 9000, Ghent, Belgium

    Hans De Meyer

Authors
  1. José De Jesús Arias García
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  2. Hans De Meyer
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  3. Bernard De Baets
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Corresponding author

Correspondence to José De Jesús Arias García .

Editor information

Editors and Affiliations

  1. Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy

    Maria Brigida Ferraro

  2. Department of Statistical Sciences, Sapienza University of Rome, Roma, Italy

    Paolo Giordani

  3. Dept of Basic & Applied Sciences Engg, Sapienza University of Rome, Rome, Italy

    Barbara Vantaggi

  4. Dept of Stoc Metds,Polish Academy of Sci, Systems Research Institute, Warsaw, Poland

    Marek Gagolewski

  5. Dept of Statis&OR and MD, Univ de Oviedo, Oviedo, Spain

    María Ángeles Gil

  6. Dept of Stoc Metds,Polish Aca of Science, Systems Res Inst, Warsaw, Poland

    Przemysław Grzegorzewski

  7. Sys Res Inti, Dept of Stoch Methods, Polish Acadmy Sci in Warsaw, Warsaw, Poland

    Olgierd Hryniewicz

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Arias García, J.D.J., De Meyer, H., De Baets, B. (2017). On the Construction of Radially Symmetric Trivariate Copulas. In: Ferraro, M., et al. Soft Methods for Data Science. SMPS 2016. Advances in Intelligent Systems and Computing, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-42972-4_2

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  • DOI: https://doi.org/10.1007/978-3-319-42972-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42971-7

  • Online ISBN: 978-3-319-42972-4

  • eBook Packages: EngineeringEngineering (R0)

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