Minimax linear, ridge and shrunken estimators for linear parameters
- 1 January 1975
- journal article
- research article
- Published by Informa UK Limited in Mathematische Operationsforschung und Statistik
- Vol. 6 (5), 697-701
- https://doi.org/10.1080/02331887508801249
Abstract
For a linear model with restrictions of the normed linear parameter to a generalized ellipsoid it is proven, that the Kuks-Olman estimator is minimax linear with respect to the matrik risk. From this follow optimal ridge and shrunken estimators.Keywords
This publication has 5 references indexed in Scilit:
- A minimax linear estimator for linear parameters under restrictions in form of inequalitiesMathematische Operationsforschung und Statistik, 1975
- On Biased Estimation in Linear ModelsTechnometrics, 1973
- Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear EstimationTechnometrics, 1970
- Ridge Regression: Biased Estimation for Nonorthogonal ProblemsTechnometrics, 1970
- Optimale vorhersage und schätznng in regulären und singulären regressionsmodellenMathematische Operationsforschung und Statistik, 1970