Conditioning on an extreme component: Model consistency with regular variation on cones

Details Conditioning on an extreme component: Model consistency with regular variation on cones Conditioning on an extreme component: Model consistency with regular variation on cones

2008-05-28

arxiv.org/abs/0805.4373v3

Bernoulli 2011, Vol. 17, No. 1, 226-252

Mathematics

Probability

Published in at http://dx.doi.org/10.3150/10-BEJ271 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statisti

Scientific paper

10.3150/10-BEJ271

Multivariate extreme value theory assumes a multivariate domain of attraction condition for the distribution of a random vector. This necessitates that each component satisfies a marginal domain of attraction condition. An approximation of the joint distribution of a random vector obtained by conditioning on one of the components being extreme was developed by Heffernan and Tawn [12] and further studied by Heffernan and Resnick [11]. These papers left unresolved the consistency of different models obtained by conditioning on different components being extreme and we here provide clarification of this issue. We also clarify the relationship between these conditional distributions, multivariate extreme value theory and standard regular variation on cones of the form $[0,\infty]\times(0,\infty]$.

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