caa a22 4500 477076564 CHVBK 20180405111440.0 cr unu---uuuuu 170330e19960401xx s 000 0 eng 10.1007/BF00046994 doi (NATIONALLICENCE)springer-10.1007/BF00046994 Minimax adjustment technique in a parameter restricted linear model [Elektronische Daten] [Peter Stahlecker, Henning Knautz, Götz Trenkler] We consider an approach yielding a minimax estimator in the linear regression model with a priori information on the parameter vector, e.g., ellipsoidal restrictions. This estimator is computed directly from the loss function and can be motivated by the general Pitman nearness criterion. It turns out that this approach coincides with the projection estimator which is obtained by projecting an initial arbitrary estimate on the subset defined by the restrictions. Kluwer Academic Publishers, 1996 linear regression nationallicence minimax adjustment nationallicence projection estimator nationallicence Stahlecker Peter Department of Economics, University of Hamburg, Germany aut Knautz Henning Department of Economics, University of Hamburg, Germany aut Trenkler Götz Department of Statistics, University of Dortmund, Germany aut Acta Applicandae Mathematica Kluwer Academic Publishers 43/1(1996-04-01), 139-144 0167-8019 43:1<139 1996 43 10440 https://doi.org/10.1007/BF00046994 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00046994 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Stahlecker Peter Department of Economics, University of Hamburg, Germany aut NATIONALLICENCE 700 1- Knautz Henning Department of Economics, University of Hamburg, Germany aut NATIONALLICENCE 700 1- Trenkler Götz Department of Statistics, University of Dortmund, Germany aut NATIONALLICENCE 773 0- Acta Applicandae Mathematica Kluwer Academic Publishers 43/1(1996-04-01), 139-144 0167-8019 43:1<139 1996 43 10440 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer