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Exact Linear Restrictions on Parameters in the General Linear Model with a Singular Covariance Matrix

 

作者: RudolfG. Kreijger,   Heinz Neudecker,  

 

期刊: Journal of the American Statistical Association  （Taylor Available online 1977）
卷期: Volume 72, issue 358  

页码: 430-432

 

ISSN:0162-1459

 

年代: 1977

 

DOI:10.1080/01621459.1977.10481014

 

出版商: Taylor & Francis Group

 

关键词: Restricted linear estimation;Singular covariance matrix

 

数据来源: Taylor

 

摘要:

An attempt is made to develop a best linear unbiased estimator of β in the modely=Xβ +u, with known singular covariance matrixVofuand restrictions on β. Two operational criteria for optimality are considered: minimum expected quadratic loss and minimum generalized variance. It is shown that these criteria lead to the same estimator, the well-known least-squares estimator, as developed by Theil (1971).

 

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