Northrop, PJ;
(2015)
An efficient semiparametric maxima estimator of the extremal index.
Extremes: statistical theory and applications in science, engineering and economics
, 18
(4)
pp. 585-603.
10.1007/s10687-015-0221-5.
Text
Northrop2015_extremes_eps.pdf Available under License : See the attached licence file. Download (150kB) |
Abstract
The extremal index θ, a measure of the degree of local dependence in the extremes of a stationary process, plays an important role in extreme value analyses. We estimate $\theta$ semiparametrically, using the relationship between the distribution of block maxima and the marginal distribution of a process to define a semiparametric model. We show that these semiparametric estimators are simpler and substantially more efficient than their parametric counterparts. We seek to improve efficiency further using maxima over sliding blocks. A simulation study shows that the semiparametric estimators are competitive with the leading estimators. An application to sea-surge heights combines inferences about $\theta$ with a standard extreme value analysis of block maxima to estimate marginal quantiles.
Type: | Article |
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Title: | An efficient semiparametric maxima estimator of the extremal index |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1007/s10687-015-0221-5 |
Publisher version: | http://link.springer.com/article/10.1007/s10687-01... |
Language: | English |
Additional information: | The final publication is available at Springer via http://dx.doi.org/10.1007/s10687-015-0221-5 |
Keywords: | block maxima, extremal index, extreme value theory, sea-surge heights, semiparametric estimation |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/1469907 |
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