JSM 2011 Online Program

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Abstract Details

Activity Number: 525
Type: Contributed
Date/Time: Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #302805
Title: Nonparametric Regression Modeling of Extreme Events
Author(s): Betül Kan*+ and Ahmet Sezer and Berna Yazici
Companies: Anadolu University and Anadolu University and Anadolu University
Address: Yunus Emre Kampüsü, Fen Fakültesi, Eskisehir, 26470, Turkey
Keywords: nonparametric ; extreme ; likelihood ratio ; Gumbel distribution
Abstract:

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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