scholarly journals Extreme Value Estimation for Heterogeneous Data

Author(s):  
John H.J. Einmahl ◽  
Yi He
2014 ◽  
Vol 140 (9) ◽  
pp. 04014061 ◽  
Author(s):  
M. F. Huang ◽  
Wenjuan Lou ◽  
Xiaotao Pan ◽  
C. M. Chan ◽  
Q. S. Li

Author(s):  
Ryota Wada ◽  
Takuji Waseda

Extreme value estimation of significant wave height is essential for designing robust and economically efficient ocean structures. But in most cases, the duration of observational wave data is not efficient to make a precise estimation of the extreme value for the desired period. When we focus on hurricane dominated oceans, the situation gets worse. The uncertainty of the extreme value estimation is the main topic of this paper. We use Likelihood-Weighted Method (LWM), a method that can quantify the uncertainty of extreme value estimation in terms of aleatory and epistemic uncertainty. We considered the extreme values of hurricane-dominated regions such as Japan and Gulf of Mexico. Though observational data is available for more than 30 years in Gulf of Mexico, the epistemic uncertainty for 100-year return period value is notably large. Extreme value estimation from 10-year duration of observational data, which is a typical case in Japan, gave a Coefficient of Variance of 43%. This may have impact on the design rules of ocean structures. Also, the consideration of epistemic uncertainty gives rational explanation for the past extreme events, which were considered as abnormal. Expected Extreme Value distribution (EEV), which is the posterior predictive distribution, defined better extreme values considering the epistemic uncertainty.


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