MSE-improvement of the least squares estimator by dropping variables

DOI10.1007/BF02613689zbMath0776.62056OpenAlexW2047574320MaRDI QIDQ685762

Götz Trenkler, Erkki P. Liski

Publication date: 18 October 1993

Published in: Metrika (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/176472

zbMATH Keywords

reduced modeldropping variablesfull modelmean shift modelmean squared error superioritymean squared error-matrix criterionuniformly most powerful \(F\)-statisticvariance of the least squares estimator

Mathematics Subject Classification ID

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

Cites Work

• Unnamed Item
• Unnamed Item
• Ordering of nonnegative definite matrices with application to comparison of linear models
• Mean square error matrix improvements and admissibility of linear estimators
• Contamination in linear regression models and its influence on estimators
• A further note on a theorem on the difference of the generalized inverses of two nonnegative definite matrices
• A Test of the Mean Square Error Criterion for Restrictions in Linear Regression

This page was built for publication: MSE-improvement of the least squares estimator by dropping variables