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Copula Estimation

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Copula Theory and Its Applications

Part of the book series: Lecture Notes in Statistics ((LNSP,volume 198))

Abstract

This chapter provides a survey of estimation methods for copula models. We review parametric, semiparametric and nonparametric approaches to inference on copulas for random samples with dependent components and copula-based time series. Among other topics, the survey discusses several problems of robust statistical analysis for copula models.

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Acknowledgements

Ibragimov gratefully acknowledges partial support provided by the National Science Foundation grant SES-0820124.

Author information

Authors and Affiliations

  1. Institute for Statistics and Econometrics, Humboldt-Universität zu Berlin, Berlin, Germany

    Barbara Choroś

  2. Department of Economics, Harvard University, Cambridge, MA, USA

    Rustam Ibragimov

  3. N. G. Chebotarev Research Institute of Mathematics and Mechanics, Kazan State University, Kazan, Russia

    Elena Permiakova

Authors
  1. Barbara Choroś
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  2. Rustam Ibragimov
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  3. Elena Permiakova
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Corresponding author

Correspondence to Barbara Choroś .

Editor information

Editors and Affiliations

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

    Piotr Jaworski

  2. , Department of Knowledge-Based, Johannes Kepler Universität, Altenberger Straße 69, Linz, 4040, Austria

    Fabrizio Durante

  3. Ladislaus von Bortkiewicz Chair of Stati, C.A.S.E. Centre for Applied Statistics a, Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin, 10099, Germany

    Wolfgang Karl Härdle

  4. , Mathematical Institute, Polish Academy of Sciences, ul. Chopina 12, Toruń, 87100, Poland

    Tomasz Rychlik

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Choroś, B., Ibragimov, R., Permiakova, E. (2010). Copula Estimation. In: Jaworski, P., Durante, F., Härdle, W., Rychlik, T. (eds) Copula Theory and Its Applications. Lecture Notes in Statistics(), vol 198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12465-5_3

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