Abstract Details
Activity Number:
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248
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Computing
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Abstract #312503
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Title:
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A Unified Approach to Shrinkage Estimation in Linear Regression Models
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Author(s):
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Enayetur Raheem*+ and Syed Ejaz Ahmed
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Companies:
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University of Northern Colorado and Brock University
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Keywords:
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Shrinkage estimation ;
James-Stein estimator ;
positive-rule shrinkage ;
Restricted estimator
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Abstract:
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We propose a somewhat unified James-Stein-type shrinkage estimator for linear regression models. In this approach, an empirical restricted estimator is introduced. A tuning parameter, which is to be estimated from the data, is proposed that controls the amount of shrinkage. At the lower extreme when the tuning parameter is zero, we get OLS estimates. At the other extreme, when it is equal to the test statistic, we obtain restricted estimator.
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Authors who are presenting talks have a * after their name.
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