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The estimation of an unknown parameter vector in a Gaussian linear model is studied in this paper. Two different cases are analyzed: the parameter vector is assumed to lie either in or on a given ellipsoid. The best estimator in terms of the mean squared error is derived. The performance of this estimator is analyzed and compared with the ordinary least squares, the constrained least squares and the linear minimax approach.doi:10.1109/icassp.2009.4960317 dblp:conf/icassp/UhlichY09 fatcat:5xychmbrgvcpbjwzmcapwj7c5q