Selecting a double \(k\)-class estimator for regression coefficients

DOI10.1016/0167-7152(93)90029-IzbMath0791.62070OpenAlexW1973284788MaRDI QIDQ1324572

V. Pereyra

Publication date: 24 May 1994

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(93)90029-i

zbMATH Keywords

elasticityStein-rule estimatorsleast squares estimatordominationminimum riskchoice of scalarsdouble \(k\)-class estimatorsfeasible choice

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items (6)

Risk and Pitman closeness properties of feasible generalized double \(k\)-class estimators in linear regression models with non-spherical disturbances under balanced loss function ⋮ ON THE USE OF THE STEIN VARIANCE ESTIMATOR IN THE DOUBLE k-CLASS ESTIMATOR IN REGRESSION ⋮ Shrinkage estimation in spatial autoregressive model ⋮ Goodness of fit for generalized shrinkage estimation ⋮ Performance of double \(k\)-class estimators for coefficients in linear regression models with non-spherical disturbances under asymmetric losses ⋮ Double \(k\)-class estimators in regression models with non-spherical disturbances

Cites Work

• A necessary and sufficient condition for the dominance of an improved family of estimators in linear regression models
• Correction to: Improved Stein-rule estimator for regression problems
• Double k-Class Estimators of Coefficients in Linear Regression
• Improved Stein-rule estimator for regression problems

This page was built for publication: Selecting a double \(k\)-class estimator for regression coefficients