Superiority of the \(r\)-\(d\) class estimator over some estimators by the mean square error matrix criterion

DOI10.1016/j.spl.2006.08.012zbMath1112.62052OpenAlexW2034346179MaRDI QIDQ876991

Selahattin Kaçıranlar, M. Revan Özkale

Publication date: 19 April 2007

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

Full work available at URL: https://doi.org/10.1016/j.spl.2006.08.012

zbMATH Keywords

multicollinearityordinary least squares estimatorLiu estimator\(r\)-\(k\) class estimatorprincipal components regression estimator

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Hypothesis testing in multivariate analysis (62H15)

Related Items

Stochastic restricted Liu predictors in linear mixed models, Combining two-parameter and principal component regression estimators, Robust ridge and robust Liu estimator for regression based on the LTS estimator, Combining the unrestricted estimators into a single estimator and a simulation study on the unrestricted estimators, On the restrictedr–kclass estimator and the restrictedr–dclass estimator in linear regression, Combining the Liu-type estimator and the principal component regression estimator, On a principal component two-parameter estimator in linear model with autocorrelated errors, r-d Class Estimator Under Misspecification, The \(\mathrm{r}\)-\(\mathrm{d}\) class predictions in linear mixed models, Improvement of the Liu Estimator in Weighted Mixed Regression, On the Principal Component Liu-type Estimator in Linear Regression

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonnegative and positive definiteness of matrices modified by two matrices of rank one
• Mean square error matrix comparison of some estimators in linear regressions with multicollinearity
• Linear models. Least squares and alternatives
• Mean squared error matrix comparisons between biased estimators — An overview of recent results
• A note on combining ridge and principal component regression
• Generalized mean squared error comparisons of biased regression estimators
• A new class of blased estimate in linear regression
• On the almost unbiased generalized liu estimator and unbiased estimation of the bias and mse
• COMBINING THE LIU ESTIMATOR AND THE PRINCIPAL COMPONENT REGRESSION ESTIMATOR
• MEAN SQUARED ERROR COMPARISONS OF SOME BIASED REGRESSION ESTIMATORS