Numerical methods for linear minimax estimation

• Autorzy: Norbert Gaffke , Berthold Heiligers
• Języki publikacji: EN

Abstrakty

EN

We discuss two numerical approaches to linear minimax estimation in linear models under ellipsoidal parameter restrictions. The first attacks the problem directly, by minimizing the maximum risk among the estimators. The second method is based on the duality between minimax and Bayes estimation, and aims at finding a least favorable prior distribution.

Słowa kluczowe

EN

Bayes estimation; duality; linear model; L-optimality; mean squared error; minimax estimation; non-smooth optimization; parameter restrictions; p-mean; quasi Newton method

• Wydawca: Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra
• Czasopismo: Discussiones Mathematicae Probability and Statistics
• Rocznik: 2000
• Tom: 20
• Numer: 1
• Strony: 51-62

Daty

wydano

2000

otrzymano

1998-11-25

Twórcy

autor

Norbert Gaffke

• Fakultät für Mathematik, Institut für Mathematische Stochastik, Universität Magdeburg, D-39106 Magdeburg, Germany

autor

Berthold Heiligers

• Fakultät für Mathematik, Institut für Mathematische Stochastik, Universität Magdeburg, D-39106 Magdeburg, Germany

Bibliografia

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Identyfikatory

DOI

10.7151/dmps.1003