Mean square error matrix comparisons of estimators in linear regression

DOI10.1080/03610928508829058zbMath0594.62075OpenAlexW2077230820MaRDI QIDQ3725372

Götz Trenkler

Publication date: 1985

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928508829058

zbMATH Keywords

pretest estimatorsmean square error matrixbiased estimationrestricted leastsquares estimator

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Point estimation (62F10)

Related Items (19)

Shrinking toward submodels in regression ⋮ Covariance adjustment in biased estimation ⋮ Local improvement of best linear unbiased estimation and admissibility under the weakly singular gauss-markov model ⋮ A test of the mean square error criterion for linear admissible estimators ⋮ Superiority comparisons between mixed regression estimators ⋮ Mean squared error matrix comparisons between biased estimators — An overview of recent results ⋮ Mean square error matrix comparison of some estimators in linear regressions with multicollinearity ⋮ A generalization and Bayesian interpretation of ridge-type estimators with good prior means ⋮ A minimum matrix valued risk estimator combining restricted and ordinary least squares estimators ⋮ On least squares estimation with a particular linear function of the dependent variable ⋮ A Bayesian approach with generalized ridge estimation for high-dimensional regression and testing ⋮ Pre-test procedures and forecasting in the regression model under restrictions ⋮ Mean square error matrix improvements and admissibility of linear estimators ⋮ Generalized preliminary test stochastic restricted estimator in the linear regression model ⋮ MSEM dominance of estimators in two seemingly unrelated regressions ⋮ On contractions in linear regression ⋮ Nonnegative and positive definiteness of matrices modified by two matrices of rank one ⋮ A stochastic restrictedk–dclass estimator ⋮ Another look at the naive estimator in a regression model

Cites Work

• On comparing restricted least squares estimators
• On the performance of biased estimators in the linear regression model with correlated or heteroscedastic errors
• Comparisons among regression estimators under the generalized mean square error criterion
• A Note on Superiority Comparisons of Homogeneous Linear Estimators
• Generalized mean squared error comparisons of biased regression estimators
• Superiority comparisons of homogeneous linear estimators
• A Test of the Mean Square Error Criterion for Restrictions in Linear Regression
• Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
• Weaker Criteria and Tests for Linear Restrictions in Regression
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