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Pairwise and Global Dependence in Trivariate Copula Models

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Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 444))

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Abstract

We investigate whether pairwise dependence properties related to all the bivariate margins of a trivariate copula imply the corresponding trivariate dependence property. The main finding is that, in general, information about the pairwise dependence is not sufficient to infer some aspects of global dependence. In essence, dependence is a multi-facet property that cannot be easily reduced to simplest cases.

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Author information

Authors and Affiliations

  1. School of Economics and Management, Free University of Bozen-Bolzano, Bolzano, Italy

    Fabrizio Durante

  2. Department of Mathematical Sciences, Lewis and Clark College, Portland, OR, 97219, USA

    Roger B. Nelsen

  3. Department of Applied Mathematics, University of Granada, Granada, Spain

    José Juan Quesada-Molina

  4. Department of Mathematics, University of Almería, Almería, Spain

    Manuel Úbeda-Flores

Authors
  1. Fabrizio Durante
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  2. Roger B. Nelsen
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  3. José Juan Quesada-Molina
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  4. Manuel Úbeda-Flores
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Editor information

Editors and Affiliations

  1. University Montpellier 2, LIRMM - CNRS UMR 5506, 161, Rue Ada, 34392, Montpellier Cedex 5, France

    Anne Laurent

  2. Institute for Human Factors and Technology Management, IAT, University of Stuttgart, Nobelstraße 12, 70569, Stuttgart, Germany

    Oliver Strauss

  3. LIP6, UPMC Univ. Paris 06, CNRS UMR 7606, F-75005, Paris, France

    Bernadette Bouchon-Meunier

  4. Dept. of Information Systems, Iona College, 710 North Ave, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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© 2014 Springer International Publishing Switzerland

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Durante, F., Nelsen, R.B., Quesada-Molina, J.J., Úbeda-Flores, M. (2014). Pairwise and Global Dependence in Trivariate Copula Models. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 444. Springer, Cham. https://doi.org/10.1007/978-3-319-08852-5_25

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  • DOI: https://doi.org/10.1007/978-3-319-08852-5_25

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08851-8

  • Online ISBN: 978-3-319-08852-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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