This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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539
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Type:
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Contributed
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Date/Time:
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Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Quality and Productivity
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Abstract - #306836 |
Title:
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A Practical Approach for Removing Multiple Outliers Using the T-Square Statistic
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Author(s):
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John C. Young and Robert L. Mason*+ and Youn-Min Amanda Chou
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Companies:
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Retired and Southwest Research Institute and The University of Texas at San Antonio
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Address:
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, San Antonio, TX, ,
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Keywords:
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Multivariate Statistical Process Control ;
Masking ;
Swamping
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Abstract:
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The occurrence of certain patterns of multiple outliers may produce problems that weaken the ability of the T-square statistic to detect potential outliers in a Phase I operation. The most prominent of these are the problems of masking and swamping. A number of robust procedures have been developed as solutions to these two problems. However, the application of the majority of these procedures to a multivariate process is not easily accomplished. We propose a procedure based on the T-square statistic that addresses both the masking and swamping problems, and is easy to apply. Industrial data are used to illustrate the proposed multiple outlier detection procedure.
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