Optimal critical values of pre-tests when estimating the regression error variance: Analytical findings under a general loss structure

DOI10.1016/S0304-4076(02)00224-5zbMath1014.62081MaRDI QIDQ1871564

Alan T. K. Wan, Guo Hua Zou

Publication date: 4 May 2003

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

zbMATH Keywords

riskLINEX lossentropy lossquadratic losslinear restrictionsLebesgue integrablefirst-order differentiablevariance homogeneity

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Point estimation (62F10)

Related Items (9)

Estimating the error variance after a pre-test for an interval restriction on the coefficients ⋮ Performance of preliminary test estimators for error variance based on W, LR and LM tests ⋮ A pre-test like estimator dominating the least-squares method ⋮ Stein-type improved estimation of standard error under asymmetric LINEX loss function ⋮ On the sensitivity of pre-test estimators to covariance misspecification ⋮ Further results on optimal critical values of pre‐test when estimating the regression error variance ⋮ Optimum Critical Value for Pre-Test Estimator ⋮ Weighted-Average Least Squares Prediction ⋮ Interval Estimation by Frequentist Model Averaging

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Optimal levels of significance of a pre-test in estimating the disturbance variance after the pre-test for a linear hypothesis on coefficients in a linear regression
• Preliminary-test estimation of the scale parameter in a mis-specified regression model
• Estimating the error variance in regression after a preliminary test of restrictions on the coefficients
• Simultaneous estimation of Poisson means under entropy loss
• Entropy loss and risk of improved estimators for the generalized variance and precision
• Improved estimation of the disturbance variance in a linear regression model
• Estimation of regression coefficients after a preliminary test for homoscedasticity
• Pre-testing for linear restrictions in a regression model with spherically symmetric disturbances
• Risk behavior of variance estimators in multivariate normal distribution
• Estimation of the error variance after a preliminary-test of homogeneity in a regression model with spherically symmetric disturbances
• Estimation of variance after a preliminary test of homogeneity and optimal levels of significance for the pre-test
• Bayesian estimation of the linear regression model with an uncertain interval constraint on coefficients
• Risk of a homoscedasticity pre-test estimator of the regression scale under LINEX loss
• Estimating the error variance after a pre-test for an inequality restriction on the coefficients
• The Traditional Pretest Estimator
• Estimation of the variance in a normal population after the one-sided pre-test for the mean
• Bayesian Estimation and Prediction Using Asymmetric Loss Functions
• On the Use of a Regret Function to Set Significance Points in Prior Tests of Estimation
• Optimal Critical Values for Pre-Testing in Regression
• Using simulation methods for bayesian econometric models: inference, development,and communication
• Preliminary-test estimation of the regression scale parameter when the loss function is asymmetric
• Inadmissibility of the Usual Estimators of Scale parameters in Problems with Unknown Location and Scale Parameters
• THE ESTIMATION OF THE LOCATION AND SCALE PARAMETERS OF A CONTINUOUS POPULATION OF ANY GIVEN FORM

This page was built for publication: Optimal critical values of pre-tests when estimating the regression error variance: Analytical findings under a general loss structure