Some conditions for optimality of the almost unbiased estimators of regression coefficients

DOI10.1080/03610928708829466zbMath0649.62063OpenAlexW2060550027MaRDI QIDQ3795083

Balakrishna S. Hosmane

Publication date: 1987

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

Full work available at URL: https://doi.org/10.1080/03610928708829466

zbMATH Keywords

biasmean square error matrixordinarysmall disturbance approximationsalmost unbiased estimator of regression coefficientsalmost unbiased ordinary ridge estimators

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (1)

Impacts of equi-correlated responses on multicollinearity

Cites Work

• Unnamed Item
• A class of almost unbiased and efficient estimators of regression coefficients
• On the asymptotic bias and mean squared error of an improved estimator for coefficients in linear regression
• On small sample properties of the almost unbiased generalized ridge estimator
• Double k-Class Estimators of Coefficients in Linear Regression
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Comparison of k-Class Estimators When the Disturbances Are Small

This page was built for publication: Some conditions for optimality of the almost unbiased estimators of regression coefficients