This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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474
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Type:
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Contributed
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Date/Time:
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Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #307320 |
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Title:
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Statistical Methods for Estimating a Minimum
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Author(s):
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Shiyao Liu*+ and William Q. Meeker
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Companies:
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Iowa State University and Iowa State University
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Address:
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3426 Orion Dr. Apt 210, Ames, IA, 50010,
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Keywords:
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Block Minima ;
Extreme value ;
Maximum likelihood ;
Simulation
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Abstract:
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Pipeline integrity is an important concern because leaks can result in serious economic or environmental losses. Periodic inspection information at a given set of locations can be used to estimate corrosion levels and rates. Traditional statistical methodology is to estimate parameters of a specified corrosion distribution and then to use these parameters to estimate the minimum thickness in a pipeline. Inferences using this method are, however, highly sensitive to the distributional assumption. Extreme value theory provides a more robust method of estimation. In particular, the block minima method from extreme value analysis can be used to estimate the minimum thickness, but one must choose the size of the blocks to be used in the analysis. In this paper we use simulation to compare the properties of different models for estimating minima pipeline thickness and investigate the effect
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