Estimating the error variance after a pre-test for an interval restriction on the coefficients

DOI10.1016/j.csda.2011.01.019zbMath1328.62144OpenAlexW2049796832MaRDI QIDQ901628

Sherry Z. F. Zhou, Rong Zhu

Publication date: 12 January 2016

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.01.019

zbMATH Keywords

pre-testmodel misspecificationerror varianceinterval restriction

Mathematics Subject Classification ID

Point estimation (62F10) Bootstrap, jackknife and other resampling methods (62F40)

Related Items (2)

Comparisons of variance estimators in a misspecified linear model with elliptically contoured errors ⋮ Comparisons of estimators for regression coefficient in a misspecified linear model with elliptically contoured errors

Uses Software

• bootstrap

Cites Work

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• The bias of the least squares estimator over interval constraints
• 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
• Estimating the error variance in regression after a preliminary test of restrictions on the coefficients
• Bootstrap methods: another look at the jackknife
• Bayesian estimation of the linear regression model with an uncertain interval constraint on coefficients
• The exact density and distribution functions of the inequality constrained and pre-test estimators
• On the sampling performance of an inequality pre-test estimator of the regression error variance under LINEX loss
• Optimal critical values of pre-tests when estimating the regression error variance: Analytical findings under a general loss structure
• Estimating the error variance after a pre-test for an inequality restriction on the coefficients
• Minimum mean-squared error estimation in linear regression with an inequality constraint
• Mean square error and efficiency of the least squares estimator over interval constraints
• Finite sample moments of a bootstrap estimator of the james-stein rule
• On the Sampling Performance of an Improved Stein Inequality Restricted Estimator
• On the bias and mean square error of the least square estimator in a regression model with two inequality constraints and multivariate t error terms
• The non-optimality of interval restricted and pre-test estimators under squared error loss
• Further results on optimal critical values of pre‐test when estimating the regression error variance
• Risk comparison of the inequality constrained least squares and other related estimators under balanced loss

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