On Minimax Estimation in Linear Regression Models with Ellipsoidal Constraints
AbstractWe consider the simultaneous linear minimax estimation problem in linear models with ellipsoidal constraints imposed on the unknown parameter. Using convex analysis we derive necessary and sufficient optimality conditions for a matrix to define the best linear minimax estimator. For certain regions of the set of characteristics of the linear models and the constraints we exploit these optimality conditions and get explicit formulae for best linear minimax estimators.
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Bibliographic InfoPaper provided by University of Bonn, Germany in its series Discussion Paper Serie B with number 205.
Length: 17 pages
Date of creation: Oct 1991
Date of revision:
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- Christopeit, N. & V. L. Girko, 1995. "Minimax Estimator for linear models with nonrandom disturbances," Discussion Paper Serie B, University of Bonn, Germany 359, University of Bonn, Germany.
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