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Characterizing extremal dependence on a hyperplane

Phyllis Wan

Biometrika2026https://doi.org/10.1093/biomet/asag015article
AJG 4ABDC A*
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0.50

Abstract

Summary In this paper, we characterize the extremal dependence of d asymptotically dependent variables using a class of random vectors on the (d-1) -dimensional hyperplane perpendicular to the diagonal vector 1 = (1,… ,1). This translates analyses of multivariate extremes to analyses on a linear vector space, opening up possibilities for applying existing statistical techniques based on linear operations. As an example, we demonstrate how to obtain lower-dimensional approximations of tail dependence through principal component analysis. Additionally, we show that the widely used Hüsler–Reiss family is characterized by a Gaussian family residing on the hyperplane.

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https://doi.org/https://doi.org/10.1093/biomet/asag015

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@article{phyllis2026,
  title        = {{Characterizing extremal dependence on a hyperplane}},
  author       = {Phyllis Wan},
  journal      = {Biometrika},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/biomet/asag015},
}

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Characterizing extremal dependence on a hyperplane

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0.50

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F · citation impact0.50 × 0.4 = 0.20
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R · text relevance †0.50 × 0.4 = 0.20

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