On the performance of biased estimators in the linear regression model with correlated or heteroscedastic errors

DOI10.1016/0304-4076(84)90045-9zbMath0559.62054OpenAlexW1997227184MaRDI QIDQ2266321

Götz Trenkler

Publication date: 1984

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(84)90045-9

zbMATH Keywords

shrinkage estimatorscorrelated errorsordinary least squares estimatorgeneralized least squares estimatorheteroscedastic errorsbiased estimatorsmean square error criteria

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items (32)

Feasible generalized Stein-rule restricted ridge regression estimators ⋮ A restricted \(r\)-\(k\) class estimator in the mixed regression model with autocorrelated disturbances ⋮ Influence measures in ridge regression when the error terms follow an AR(1) process ⋮ General ridge predictors in a mixed linear model ⋮ Ridge regression estimators in the linear regression models with non-spherical errors ⋮ Mean square error matrix comparisons of estimators in linear regression ⋮ A Simulation Study of Ridge Regression Estimators with Autocorrelated Errors ⋮ Ridge estimation in linear models with heteroskedastic errors ⋮ Efficiency of the generalized restricted difference-based almost unbiased ridge estimator in partially linear model ⋮ Regression diagnostics methods for Liu estimator under the general linear regression model ⋮ Simultaneous prediction using target function based on principal components estimator with correlated errors ⋮ The feasible generalized restricted ridge regression estimator ⋮ Efficiency of a generalized difference-based weighted mixed ridge estimator in partially linear model ⋮ A generalized difference-based mixed two-parameter estimator in partially linear model ⋮ Ridge estimator with correlated errors and two-stage ridge estimator under inequality restrictions ⋮ Influence measures based on confidence ellipsoids in general linear regression model with correlated regressors ⋮ Improvement of generalized difference-based mixed Liu estimator in partially linear model ⋮ On the Performance of the Jackknifed Modified Ridge Estimator in the Linear Regression Model with Correlated or Heteroscedastic Errors ⋮ A note on the performance of biased estimators with autocorrelated errors ⋮ A jackknifed ridge estimator in the linear regression model with heteroscedastic or correlated errors ⋮ Performance of Kibria's Method for the Heteroscedastic Ridge Regression Model: Some Monte Carlo Evidence ⋮ Monte Carlo Simulation Study of Biased Estimators in the Linear Regression Models with Correlated or Heteroscedastic Errors ⋮ On a principal component two-parameter estimator in linear model with autocorrelated errors ⋮ A Further Study of Predictions in Linear Mixed Models ⋮ A Comparison of Mixed and Ridge Estimators of Linear Models ⋮ \(r\)-\(k\) class estimator in the linear regression model with correlated errors ⋮ Cross validation of ridge regression estimator in autocorrelated linear regression models ⋮ A Class of s–K Type Principal Components Estimators in the Linear Model ⋮ A stochastic restricted ridge regression estimator ⋮ Comparisons among three estimation methods in linear models when observations are pairwise correlated ⋮ Mixed Lasso estimator for stochastic restricted regression models ⋮ Using Heteroscedasticity-Consistent Standard Errors for the Linear Regression Model with Correlated Regressors

Cites Work

• A test of the mean square error criterion for shrinkage estimators
• Comparisons among regression estimators under the generalized mean square error criterion
• A Note on Superiority Comparisons of Homogeneous Linear Estimators
• Ridge estimation in regression problems with autocorrelated errors: A monte carlo study
• Ridge Analysis Following a Preliminary Test of the Shrunken Hypothesis
• Superiority comparisons of homogeneous linear estimators
• Error misspecification and properties of the simple ridge estimator
• Quadratic Forms and Idempotent Matrices with Random Elements
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
• On Biased Estimation in Linear Models
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: On the performance of biased estimators in the linear regression model with correlated or heteroscedastic errors