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Abstract Details
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Activity Number:
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513
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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 Physical and Engineering Sciences
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| Abstract - #300782 |
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Title:
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The Liu, Ridge, and Least Square Estimators: A Comparison
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Author(s):
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Marvin Haskel Jack Gruber*+
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Companies:
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Rochester Institute of Technology
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Address:
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130 Rivermeadow Drive, Rochester, NY, 14623,
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Keywords:
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Zellner's balanced loss function ;
mean square error ;
shrinkage estimator ;
optimal estimator
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Abstract:
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In a 1993 paper Liu proposed an estimator that is similar in form but different from the ridge regression estimator of Hoerl and Kennard. More recently in 2007 Ozkale and Kaciranlar proposed a two parameter variation of the Liu estimator. We will derive a generalization of the two parameter Liu estimator that is optimal with respect to Zellner's balanced loss function (ZBLF) for prior assumptions about the first and second moment. This Liu type estimator specializes to the generalized ridge regression estimator for the classical loss function(CLF). The Bayes and the frequentist risks with respect to both ZBLF and CLF will be compared for the Liu type estimator, the ridge estimator and the least square estimator.
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