An unexpected property of minimax estimation in the relative squared error approach to linear regression analysis
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Publication:649102
DOI10.1007/S00184-010-0309-5zbMath1226.62065OpenAlexW2021817763MaRDI QIDQ649102
Bernhard F. Arnold, Peter Stahlecker
Publication date: 30 November 2011
Published in: Metrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00184-010-0309-5
ridge estimatorgeneralized least squares estimatorlinear affine estimationKuks-Olman estimatorLöwner ordering
Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Minimax procedures in statistical decision theory (62C20)
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- Least squares in general vector spaces revisited.
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- Minimax estimation in the linear model with a relative squared error
- Linear models. Least squares and alternatives
- A surprising property of uniformly best linear affine estimation in linear regression when prior information is fuzzy
- Some properties of the relative squared error approach to linear regression analysis
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