Improved estimation of the disturbance variance in a linear regression model

DOI10.1016/0304-4076(88)90065-6zbMath0677.62060OpenAlexW2034625180MaRDI QIDQ1123515

Alan E. Gelfand, Dey, Dipak K.

Publication date: 1988

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

Full work available at URL: https://doi.org/10.1016/0304-4076(88)90065-6

zbMATH Keywords

squared error lossordinary least squares estimatorestimation of the disturbance variancenew class of improved estimators

Mathematics Subject Classification ID

Linear regression; mixed models (62J05)

Related Items

Estimation of the variance and its applications ⋮ Asymmetric risk of the Stein variance estimator under a misspecified linear regression model ⋮ Risk behavior of a pre-test estimator for normal variance with the Stein- type estimator ⋮ Preliminary-test estimation of the regression scale parameter when the loss function is asymmetric ⋮ The exact distribution and density functions of the stein-type estimator for normal variance ⋮ Some modifications of improved estimators of a normal variance ⋮ ON THE USE OF THE STEIN VARIANCE ESTIMATOR IN THE DOUBLE k-CLASS ESTIMATOR IN REGRESSION ⋮ Estimation of error variance in ANOVA model and order restricted scale parameters ⋮ Further improving the Stein-rule estimator using the Stein variance estimator in a misspecified linear regression model ⋮ The exact distribution and density functions of a pre-test estimator of the error variance in a linear regression model with proxy variables ⋮ Preliminary-test estimation of the scale parameter in a mis-specified regression model ⋮ The neyman accuracy and the wolfowitz accuracy of the stein type confidence interval for the disturbance variance ⋮ The optimal size of a preliminary test for linear restrictions when estimating the regression scale parameter ⋮ Pre-testing for linear restrictions in a regression model with spherically symmetric disturbances ⋮ Comparisons of estimators for regression coefficient in a misspecified linear model with elliptically contoured errors ⋮ On a class of improved estimators of variance and estimation under order restriction ⋮ Estimation of the variance in a normal population after the one-sided pre-test for the mean ⋮ A minimum discrimination information estimator of preliminary conjectured normal variance ⋮ Estimation of Error Variance in the Analysis of Experiments Using Two-Level Orthogonal Arrays ⋮ Comparison of the Stein and the usual estimators for the regression error variance under the Pitman nearness criterion when variables are omitted ⋮ Inadmissibility of the Stein-rule estimator under the balanced loss function ⋮ Exact distribution of a pre-test estimator for regression error variance when there are omitted variables. ⋮ Optimal critical values of pre-tests when estimating the regression error variance: Analytical findings under a general loss structure

Cites Work

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• Improving on equivariant estimators
• Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean
• Inadmissibility of the Usual Estimators of Scale parameters in Problems with Unknown Location and Scale Parameters
• Mean Square Efficiency of Estimators of Variance Components
• Linear Statistical Inference and its Applications