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Abstract Details
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Activity Number:
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138
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #305208 |
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Title:
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A Minimum Quantile Estimator for the Generalized Pareto Distribution
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Author(s):
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David Smith*+
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Companies:
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Tennessee Tech University
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Address:
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806 Wall Ave, Cookeville, TN, 38501, United States
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Keywords:
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extreme value ;
exceedence ;
covariates ;
generalized linear model ;
peak over threshold
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Abstract:
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The generalized Pareto distribution has long been used to model extreme weather phenomena such wind speed, wave height, and flood levels. Until recently, the parameters of the distribution were not coupled with auxiliary information that may be treated as explanatory variables. We discuss three methods of incorporating auxiliary information into the mean of the distribution. Two methods, maximum likelihood and a Minimum Goodness of Fit approach have been previously studied. We propose a third method that is intuitively appealing, easy to compute, and utilizes a non-linear regression model framework available in most statistical software packages. Finite sample performance is investigated and followed by two example data sets.
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Authors who are presenting talks have a * after their name.
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