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Copulae in Mathematical and Quantitative Finance pp 231–249Cite as

Copula-Based Models for Multivariate Discrete Response Data

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Part of the book series: Lecture Notes in Statistics ((LNSP,volume 213))

Abstract

In this survey we review copula-based models and methods for multivariate discrete data modeling. Advantages and disadvantages of recent contributions are summarized and a general modeling procedure is suggested in this context.

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Notes

  1. 1.

    Both approximations to MVN rectangle in [18], the 1-dimensional integral in the positive exchangeable case, and the method in [50], can be computed with the functions mvnapp, exchmvn, and pmnorm, respectively, in the R package mprobit [21]. The methods in [11] can be computed with the function pmvnorm in the R package mvtnorm [12].

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Acknowledgments

I would like to thank Professor Harry Joe, University of British Columbia, for helpful comments and suggestions on an earlier version of this survey.

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Authors and Affiliations

  1. School of Computing Sciences, University of East Anglia, Norwich, UK

    Aristidis K. Nikoloulopoulos

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  1. Aristidis K. Nikoloulopoulos
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Correspondence to Aristidis K. Nikoloulopoulos .

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Editors and Affiliations

  1. Faculty of Mathematics, Informatics, and Mechanics, University of Warsaw, ul. Banacha 2, Warszawa, 02097, Poland

    Piotr Jaworski

  2. School of Economics and Management, Free University of Bozen-Bolzano, Piazza Università 1, Bozen, 39100, Italy

    Fabrizio Durante

  3. L.v.Bortkiewicz Chair of Statistics, C.A.S.E. Centre f. Appl. Stat. & Econ., Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin, 10099, Germany

    Wolfgang Karl Härdle

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Nikoloulopoulos, A.K. (2013). Copula-Based Models for Multivariate Discrete Response Data. In: Jaworski, P., Durante, F., Härdle, W. (eds) Copulae in Mathematical and Quantitative Finance. Lecture Notes in Statistics(), vol 213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35407-6_11

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