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A Note on the Kuks-Olman Estimator

 

作者: Kurt Hoffmann,  

 

期刊: Statistics  （Taylor Available online 1995）
卷期: Volume 26, issue 3  

页码: 185-187

 

ISSN:0233-1888

 

年代: 1995

 

DOI:10.1080/02331889508802488

 

出版商: Gordon & Breach Science Publishers

 

关键词: AMS subject classification;Primary 62J05;secondary 62F10;Linear regression;restricted parameter region;least squares estimation

 

数据来源: Taylor

 

摘要:

In the linear regression model the unknown parameter vectorθis supposed to vary in a known ellipsoid. Under this parameter constraint Kuks and Olman derived an estimator by demanding a minimax property. Since sometimes the Kuks-Olman estimator takes values outside of the ellipsoid a modification is proposed in the paper. It is shown that this modified variant is a least squares estimator in the restricted model.

 

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