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  • WTDE_dependence_final

    Rights statement: This is the peer reviewed version of the following article: Wadsworth, J. L., Tawn, J. A., Davison, A. C. and Elton, D. M. (2017), Modelling across extremal dependence classes. J. R. Stat. Soc. B, 79: 149–175. doi:10.1111/rssb.12157 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/rssb.12157/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

    Accepted author manuscript, 595 KB, PDF-document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

  • SuppMat_round3

    Rights statement: This is the peer reviewed version of the following article: Wadsworth, J. L., Tawn, J. A., Davison, A. C. and Elton, D. M. (2017), Modelling across extremal dependence classes. J. R. Stat. Soc. B, 79: 149–175. doi:10.1111/rssb.12157 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/rssb.12157/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

    Accepted author manuscript, 248 KB, PDF-document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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Modelling across extremal dependence classes

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>01/2017
<mark>Journal</mark>Journal of the Royal Statistical Society: Series B (Statistical Methodology)
Issue number1
Volume79
Number of pages27
Pages (from-to)149-175
<mark>State</mark>Published
Early online date17/02/16
<mark>Original language</mark>English

Abstract

Different dependence scenarios can arise in multivariate extremes, entailing careful selection of an appropriate class of models. In bivariate extremes, the variables are either asymptotically dependent or are asymptotically independent. Most available statistical models suit one or other of these cases, but not both, resulting in a stage in the inference that is unaccounted for, but can substantially impact subsequent extrapolation. Existing modelling solutions to this problem are either applicable only on sub-domains, or appeal to multiple limit theories. We introduce a unified representation for bivariate extremes that encompasses a wide variety of dependence scenarios, and applies when at least one variable is large. Our representation motivates a parametric model that encompasses both dependence classes. We implement a simple version of this model, and show that it performs well in a range of settings.

Bibliographic note

This is the peer reviewed version of the following article: Wadsworth, J. L., Tawn, J. A., Davison, A. C. and Elton, D. M. (2017), Modelling across extremal dependence classes. J. R. Stat. Soc. B, 79: 149–175. doi:10.1111/rssb.12157 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/rssb.12157/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.