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Dependence Modeling

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Inference for copula modeling of discrete data: a cautionary tale and some facts

Olivier P. Faugeras
  • Toulouse School of Economics - Université Toulouse Capitole, Manufacture des Tabacs, Bureau MF319, 21 Allée de Brienne, 31000 Toulouse, France
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Published Online: 2017-06-27 | DOI: https://doi.org/10.1515/demo-2017-0008


In this note, we elucidate some of the mathematical, statistical and epistemological issues involved in using copulas to model discrete data. We contrast the possible use of (nonparametric) copula methods versus the problematic use of parametric copula models. For the latter, we stress, among other issues, the possibility of obtaining impossible models, arising from model misspecification or unidentifiability of the copula parameter.

Keywords : copula; discrete data; parametric model; statistical inference; unidentifiability

MSC 2010: 62A01; 62H20; 62H12


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About the article

Received: 2016-12-20

Accepted: 2017-06-05

Published Online: 2017-06-27

Published in Print: 2017-01-26

Citation Information: Dependence Modeling, Volume 5, Issue 1, Pages 121–132, ISSN (Online) 2300-2298, DOI: https://doi.org/10.1515/demo-2017-0008.

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© 2017. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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