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http://dx.doi.org/10.13160/ricns.2013.6.4.251

Improvement of the Modified James-Stein Estimator with Shrinkage Point and Constraints on the Norm  

Kim, Jae Hyun (Department of Computer Engineering, Seokyeong University)
Baek, Hoh Yoo (Division of Mathematics and Informational Statistics, Wonkwang University)
Publication Information
Journal of Integrative Natural Science / v.6, no.4, 2013 , pp. 251-255 More about this Journal
Abstract
For the mean vector of a p-variate normal distribution ($p{\geq}4$), the optimal estimation within the class of modified James-Stein type decision rules under the quadratic loss is given when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}{\theta}-\bar{\theta}1{\parallel}$ it known.
Keywords
Modified James-Stein Type Decision Rule; Mean Vector; Quadratic Loss; Underlying Distribution;
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Times Cited By KSCI : 5  (Citation Analysis)
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