English

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

Probability 2011-02-11 v3 Statistics Theory Statistics Theory

Abstract

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,]×(0,][0,\infty]\times(0,\infty].

Keywords

Cite

@article{arxiv.0805.4373,
  title  = {Conditioning on an extreme component: Model consistency with regular variation on cones},
  author = {Bikramjit Das and Sidney I. Resnick},
  journal= {arXiv preprint arXiv:0805.4373},
  year   = {2011}
}

Comments

Published in at http://dx.doi.org/10.3150/10-BEJ271 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

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