Robust estimation of common regression coefficients under spherical symmetry

DOI10.1007/BF00121647zbMath0761.62037OpenAlexW1967549028MaRDI QIDQ1206620

S. Singh

Publication date: 1 April 1993

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00121647

zbMATH Keywords

common meanrobust estimationelliptically contoured distributionsGraybill-Deal estimatorStein effectheteroscedastic linear modelestimating common regression coefficientsspherical symmetry assumptionStein problem

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (2)

Estimation of noncentrality parameters ⋮ Robust minimax Stein estimation under invariant data-based loss for spherically and elliptically symmetric distributions

Cites Work

• Simultaneous estimation of location parameters under quadratic loss
• Closer estimators of a common mean in the sense of Pitman
• Robust shrinkage estimators of the location parameter for elliptically symmetric distributions
• Minimax ridge regression estimation
• Minimax estimation of location vectors for a wide class of densities
• Estimation of common coefficients in two regression equations
• Condition Numbers and Minimax Ridge Regression Estimators
• Sequential shrinkage estimation of the difference between two multivariate normal means
• Estimation of location parameters from two linear models under normality
• Combining Estimates of Location
• A note on estimating the common mean of k normal distributions and the stein problem
• Combining Unbiased Estimators
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