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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - New estimation methods for extremal bivariate return curves
AU - Murphy-Barltrop, Callum
AU - Wadsworth, Jennifer
AU - Eastoe, Emma
PY - 2023/8/31
Y1 - 2023/8/31
N2 - In the multivariate setting, estimates of extremal risk measures are important in many contexts, such as environmental planning and structural engineering. In this paper, we propose new estimation methods for extremal bivariate return curves, a risk measure that is the natural bivariate extension to a return level. Unlike several existing techniques, our estimates are based on bivariate extreme value models that can capture both key forms of extremal dependence. We devise tools for validating return curve estimates, as well as representing their uncertainty, and compare a selection of curve estimation techniques through simulation studies. We apply the methodology to two met-ocean data sets, with diagnostics indicatinggenerally good performance.
AB - In the multivariate setting, estimates of extremal risk measures are important in many contexts, such as environmental planning and structural engineering. In this paper, we propose new estimation methods for extremal bivariate return curves, a risk measure that is the natural bivariate extension to a return level. Unlike several existing techniques, our estimates are based on bivariate extreme value models that can capture both key forms of extremal dependence. We devise tools for validating return curve estimates, as well as representing their uncertainty, and compare a selection of curve estimation techniques through simulation studies. We apply the methodology to two met-ocean data sets, with diagnostics indicatinggenerally good performance.
KW - dependence modelling
KW - extremes
KW - risk measure
U2 - 10.1002/env.2797
DO - 10.1002/env.2797
M3 - Journal article
VL - 34
JO - Environmetrics
JF - Environmetrics
SN - 1180-4009
IS - 5
M1 - e2797
ER -