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Statistical measures of extremal dependence illustrated using measured sea surface elevations from a neighbourhood of coastal locations

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Statistical measures of extremal dependence illustrated using measured sea surface elevations from a neighbourhood of coastal locations. / Eastoe, Emma; Koukoulas, Sotirios; Jonathan, Philip.
In: Ocean Engineering, Vol. 62, 01.04.2013, p. 68-77.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Eastoe, E, Koukoulas, S & Jonathan, P 2013, 'Statistical measures of extremal dependence illustrated using measured sea surface elevations from a neighbourhood of coastal locations', Ocean Engineering, vol. 62, pp. 68-77. https://doi.org/10.1016/j.oceaneng.2013.01.002

APA

Eastoe, E., Koukoulas, S., & Jonathan, P. (2013). Statistical measures of extremal dependence illustrated using measured sea surface elevations from a neighbourhood of coastal locations. Ocean Engineering, 62, 68-77. https://doi.org/10.1016/j.oceaneng.2013.01.002

Vancouver

Eastoe E, Koukoulas S, Jonathan P. Statistical measures of extremal dependence illustrated using measured sea surface elevations from a neighbourhood of coastal locations. Ocean Engineering. 2013 Apr 1;62:68-77. Epub 2013 Feb 28. doi: 10.1016/j.oceaneng.2013.01.002

Author

Eastoe, Emma ; Koukoulas, Sotirios ; Jonathan, Philip. / Statistical measures of extremal dependence illustrated using measured sea surface elevations from a neighbourhood of coastal locations. In: Ocean Engineering. 2013 ; Vol. 62. pp. 68-77.

Bibtex

@article{af234b3dbf7f4a6899f7acaf51784c33,
title = "Statistical measures of extremal dependence illustrated using measured sea surface elevations from a neighbourhood of coastal locations",
abstract = "The extremal dependence of stationary time-series at pairs of locations can be summarised using one or more of a number of statistics. We illustrate the application of the coefficient of tail dependence, the $\chi$ and $\bar{\chi}$ statistics, and the conditional extremes model of Heffernan--Tawn to estimate the extremal dependence in time-series of 3-hour maxima of sea surface elevation across a spatial array of measurement gauges at the US Army Corps ofEngineers' Field Research Facility on the Atlantic coast of North Carolina. Although the original data are non-stationary, we induce stationarity on a site-by-site basis using a non-parametric model to remove the mean trend. Subsequently, we find that pairs of locations are generally asymptotically dependent. Parameter estimates for the Heffernan--Tawn model, although uncertain, suggest thatcharacteristics of conditional extremes vary systematically with distance from the conditioning site.",
keywords = "Extreme waves, Extremal dependence, Statistical models , Non-stationarity , Peaks over threshold , Generalised Pareto , Conditional extremes",
author = "Emma Eastoe and Sotirios Koukoulas and Philip Jonathan",
year = "2013",
month = apr,
day = "1",
doi = "10.1016/j.oceaneng.2013.01.002",
language = "English",
volume = "62",
pages = "68--77",
journal = "Ocean Engineering",
issn = "0029-8018",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Statistical measures of extremal dependence illustrated using measured sea surface elevations from a neighbourhood of coastal locations

AU - Eastoe, Emma

AU - Koukoulas, Sotirios

AU - Jonathan, Philip

PY - 2013/4/1

Y1 - 2013/4/1

N2 - The extremal dependence of stationary time-series at pairs of locations can be summarised using one or more of a number of statistics. We illustrate the application of the coefficient of tail dependence, the $\chi$ and $\bar{\chi}$ statistics, and the conditional extremes model of Heffernan--Tawn to estimate the extremal dependence in time-series of 3-hour maxima of sea surface elevation across a spatial array of measurement gauges at the US Army Corps ofEngineers' Field Research Facility on the Atlantic coast of North Carolina. Although the original data are non-stationary, we induce stationarity on a site-by-site basis using a non-parametric model to remove the mean trend. Subsequently, we find that pairs of locations are generally asymptotically dependent. Parameter estimates for the Heffernan--Tawn model, although uncertain, suggest thatcharacteristics of conditional extremes vary systematically with distance from the conditioning site.

AB - The extremal dependence of stationary time-series at pairs of locations can be summarised using one or more of a number of statistics. We illustrate the application of the coefficient of tail dependence, the $\chi$ and $\bar{\chi}$ statistics, and the conditional extremes model of Heffernan--Tawn to estimate the extremal dependence in time-series of 3-hour maxima of sea surface elevation across a spatial array of measurement gauges at the US Army Corps ofEngineers' Field Research Facility on the Atlantic coast of North Carolina. Although the original data are non-stationary, we induce stationarity on a site-by-site basis using a non-parametric model to remove the mean trend. Subsequently, we find that pairs of locations are generally asymptotically dependent. Parameter estimates for the Heffernan--Tawn model, although uncertain, suggest thatcharacteristics of conditional extremes vary systematically with distance from the conditioning site.

KW - Extreme waves

KW - Extremal dependence

KW - Statistical models

KW - Non-stationarity

KW - Peaks over threshold

KW - Generalised Pareto

KW - Conditional extremes

U2 - 10.1016/j.oceaneng.2013.01.002

DO - 10.1016/j.oceaneng.2013.01.002

M3 - Journal article

VL - 62

SP - 68

EP - 77

JO - Ocean Engineering

JF - Ocean Engineering

SN - 0029-8018

ER -