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Abstract Details
Activity Number:
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577
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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International Chinese Statistical Association
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Abstract - #305719 |
Title:
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Optimal Designs for Locating Regression Variables in a Multivariate Regression Model Under Trace Criteria
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Author(s):
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Chun Sui Lin*+ and Mong-Na Lo Huang and Jia-Ming Guo
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Companies:
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Cheng Shiu University and National Sun Yat-sen University and National Sun Yat-sen University
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Address:
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NO.840, Chengcing RD., Niaosong DIST.,, Kaohsiung, _, , Taiwan, Republic of China
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Keywords:
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A-criteria ;
calibration ;
equivalence theorem ;
scalar optimal design
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Abstract:
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In the literature, a fitting setup on the regression variables using information on the measured responses has been called calibration. Previous research on calibration paid little attention to the problems with regard to optimal experiment design issues. This study presents optimal designs for locating multiple regression variables in a multi-response regression model. In particular, the locations of the multiple regression variables are based on measured responses and target responses respectively. The design criterion is trace criterion which minimize the trace of the mean squared errors matrix of the estimators of regressors. The method is illustrated by an example. The comparison of the difference between the optimal designs for calibration and target location is provided and the efficiencies of the two optimal designs relative to the uniform design are also presented through the example.
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