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Meta densities and the shape of their sample clouds

Author

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  • Balkema, A.A.
  • Embrechts, P.
  • Nolde, N.

Abstract

This paper compares the shape of the level sets for two multivariate densities. The densities are positive and continuous, and have the same dependence structure. The density f is heavy-tailed. It decreases at the same rate-up to a positive constant-along all rays. The level sets {f>c} for c[downwards arrow]0, have a limit shape, a bounded convex set. We transform each of the coordinates to obtain a new density g with Gaussian marginals. We shall also consider densities g with Laplace, or symmetric Weibull marginal densities. It will be shown that the level sets of the new light-tailed density g also have a limit shape, a bounded star-shaped set. The boundary of this set may be written down explicitly as the solution of a simple equation depending on two positive parameters. The limit shape is of interest in the study of extremes and in risk theory, since it determines how the extreme observations in different directions relate. Although the densities f and g have the same copula-by construction-the shapes of the level sets are not related. Knowledge of the limit shape of the level sets for one density gives no information about the limit shape for the other density.

Suggested Citation

  • Balkema, A.A. & Embrechts, P. & Nolde, N., 2010. "Meta densities and the shape of their sample clouds," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1738-1754, August.
  • Handle: RePEc:eee:jmvana:v:101:y:2010:i:7:p:1738-1754
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Liebscher Eckhard & Richter Wolf-Dieter, 2020. "Modelling with star-shaped distributions," Dependence Modeling, De Gruyter, vol. 8(1), pages 45-69, January.
    2. Owada, Takashi, 2019. "Topological crackle of heavy-tailed moving average processes," Stochastic Processes and their Applications, Elsevier, vol. 129(12), pages 4965-4997.
    3. Eckhard Liebscher & Wolf-Dieter Richter, 2016. "Estimation of Star-Shaped Distributions," Risks, MDPI, vol. 4(4), pages 1-37, November.
    4. de Valk, Cees, 2016. "A large deviations approach to the statistics of extreme events," Other publications TiSEM 117b3ba0-0e40-4277-b25e-d, Tilburg University, School of Economics and Management.
    5. Liebscher Eckhard & Richter Wolf-Dieter, 2020. "Modelling with star-shaped distributions," Dependence Modeling, De Gruyter, vol. 8(1), pages 45-69, January.
    6. Wolf-Dieter Richter, 2019. "On (p1,…,pk)-spherical distributions," Journal of Statistical Distributions and Applications, Springer, vol. 6(1), pages 1-18, December.
    7. Wolf-Dieter Richter & Kay Schicker, 2017. "Simulation of polyhedral convex contoured distributions," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-19, December.
    8. Wolf-Dieter Richter, 2019. "High-dimensional star-shaped distributions," Journal of Statistical Distributions and Applications, Springer, vol. 6(1), pages 1-12, December.
    9. Nolde, Natalia, 2014. "Geometric interpretation of the residual dependence coefficient," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 85-95.
    10. Christian Genest & Johanna G. Nešlehová, 2020. "A Conversation With Paul Embrechts," International Statistical Review, International Statistical Institute, vol. 88(3), pages 521-547, December.
    11. E. Hashorva, 2018. "Approximation of Some Multivariate Risk Measures for Gaussian Risks," Papers 1803.06922, arXiv.org, revised Oct 2018.
    12. Simpson, Emma S. & Wadsworth, Jennifer L. & Tawn, Jonathan A., 2021. "A geometric investigation into the tail dependence of vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 184(C).

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