The pairwise beta distribution: A flexible parametric multivariate model for extremes
We present a new parametric model for the angular measure of a multivariate extreme value distribution. Unlike many parametric models that are limited to the bivariate case, the flexible model can describe the extremes of random vectors of dimension greater than two. The novel construction method relies on a geometric interpretation of the requirements of a valid angular measure. An advantage of this model is that its parameters directly affect the level of dependence between each pair of components of the random vector, and as such the parameters of the model are more interpretable than those of earlier parametric models for multivariate extremes. The model is applied to air quality data and simulated spatial data.
Year of publication: |
2010
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Authors: | Cooley, Daniel ; Davis, Richard A. ; Naveau, Philippe |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 101.2010, 9, p. 2103-2117
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Publisher: |
Elsevier |
Keywords: | Angular measure Spectral measure Multivariate regular variation Threshold exceedances |
Saved in:
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