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Abstract Details
Activity Number:
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525
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #302805 |
Title:
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Nonparametric Regression Modeling of Extreme Events
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Author(s):
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Betül Kan*+ and Ahmet Sezer and Berna Yazici
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Companies:
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Anadolu University and Anadolu University and Anadolu University
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Address:
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Yunus Emre Kampüsü, Fen Fakültesi, Eskisehir, 26470, Turkey
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Keywords:
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nonparametric ;
extreme ;
likelihood ratio ;
Gumbel distribution
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Abstract:
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Extreme value data analysis has been widely used in nonparametric regression modeling. This study aims to introduce the fundamentals of extreme value theory as well as practical aspects for estimating and evaluating the models for tail related risk measures.
The nonparametric and the linear models are taken into account to form the relationship between the temperature and time effect. The log-likelihood value has been used to evaluate the adequacy of the form of the covariate effects on real life data set. For each year from 1991 to 2010 the 15 highest daily temperature values are analyzed by using the block Gumbel distribution to investigate the global warming.
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