A comparison of minimax and least squares estimators in linear regression with polyhedral prior information

DOI10.1007/BF00046993zbMath0844.62060MaRDI QIDQ1914890

Karsten Schmidt

Publication date: 9 June 1996

Published in: Acta Applicandae Mathematicae (Search for Journal in Brave)

zbMATH Keywords

Monte Carlolinear inequalitiesparameter restrictionleast squares estimatorslinear minimax estimatorprojection estimatorsaverage performancemaximum riskinequality restricted least squares estimatorpolyhedral prior informationquasiminimax estimator

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Minimax procedures in statistical decision theory (62C20) Monte Carlo methods (65C05)

Uses Software

• Algorithm 431

Cites Work

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• Minimax estimation in linear regression with singular covariance structure and convex polyhedral constraints
• Minimax linear regression estimation with symmetric parameter restrictions
• Quasi minimax estimation in the linear regression model
• Reducing the Maximum Risk of Regression Estimators by Polyhedral Projection
• Bimatrix Equilibrium Points and Mathematical Programming
• Inequality Restrictions in Regression Analysis

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