The relationship between the improvement on the point estimation and the improvement on the interval estimation for the disturbance variance in a linear regression model

DOI10.1080/03610929508831579zbMath0937.62563OpenAlexW2091109502MaRDI QIDQ4337024

Yasushi Nagata

Publication date: 13 June 2000

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

Full work available at URL: https://doi.org/10.1080/03610929508831579

zbMATH Keywords

linear modelcoverage probabilityStein-type estimatorimprovementdisturbance varianceequal-tailed confidence intervalshortest unbiased confidence interval

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Linear regression; mixed models (62J05) Point estimation (62F10)

Related Items (4)

The neyman accuracy and the wolfowitz accuracy of the stein type confidence interval for the disturbance variance ⋮ Stein type confidence interval of the disturbance variance in a linear regression model with multivariate student-t distributed errors ⋮ On a class of improved estimators of variance and estimation under order restriction ⋮ Applied regression analysis bibliography update 1994-97

Cites Work

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• 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
• Improved confidence intervals for a normal variance
• Estimating the error variance in regression after a preliminary test of restrictions on the coefficients
• Improved invariant confidence intervals for a normal variance
• Pre-testing for linear restrictions in a regression model with spherically symmetric disturbances
• A unified approach to improving equivariant estimators
• Improving on equivariant estimators
• Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean
• Optimal Confidence Intervals for the Variance of a Normal Distribution
• The exact distribution and density functions of the stein-type estimator for normal variance
• Inadmissibility of the Usual Estimators of Scale parameters in Problems with Unknown Location and Scale Parameters
• Improved Confidence Intervals for the Variance of a Normal Distribution

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