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Comparing Stochastically Restricted Linear Estimators in a Regression Model

✍ Scribed by Dr. Erkki P. Liski


Publisher
John Wiley and Sons
Year
1989
Tongue
English
Weight
202 KB
Volume
31
Category
Article
ISSN
0323-3847

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✦ Synopsis


Conditions for superiority of the minimum dispersion estimator over another with respect to the covariance matrix are derived when the vector parameter of a regression model is subject to competing stochastic restrictions. The restrictions may also consist both of a deterministic part and a stochastic part.


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## Abstract The variance‐covariance matrices of restricted regression and mixed regression estimators are compared and the consequences of introducing variability in the restrictions are examined.