Castro-Camilo, D. and de Carvalho, M. (2017) Spectral density regression for bivariate extremes. Stochastic Environmental Research and Risk Assessment, 31(7), pp. 1603-1613. (doi: 10.1007/s00477-016-1257-z)
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Abstract
We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods.
| Item Type: | Articles |
|---|---|
| Keywords: | Bivariate extremes values, non-stationary extremal dependence structures, spectral density, statistics of extremes. |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Castro-Camilo, Dr Daniela |
| Authors: | Castro-Camilo, D., and de Carvalho, M. |
| College/School: | College of Science and Engineering > School of Mathematics and Statistics > Statistics |
| Journal Name: | Stochastic Environmental Research and Risk Assessment |
| Journal Abbr.: | SERRA |
| Publisher: | Springer |
| ISSN: | 1436-3240 |
| ISSN (Online): | 1436-3259 |
| Published Online: | 11 May 2016 |
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