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On a relationship between minimax-linear and admissible estimators in linear regression

✍ Scribed by Erkki P. Liski

Book ID
107826479
Publisher
Elsevier Science
Year
1992
Tongue
English
Weight
680 KB
Volume
176
Category
Article
ISSN
0024-3795

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πŸ“œ SIMILAR VOLUMES

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We consider the linear regression model where prior information in the form of linear inequalities restricts the parameter space to a polyhedron. Since the linear minimax estimator has, in general, to be determined numerically, it was proposed to minimize an upper bound of the maximum risk instead.

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In the paper the problem of simultaneous linear estimation of fixed and random effects in the mixed linear model is considered. A necessary and sufficient conditions for a linear estimator of a linear function of fixed and random effects in balanced nested and crossed classification models to be adm