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

DOI10.1016/0378-3758(95)00110-7zbMath0846.62051OpenAlexW1970856666MaRDI QIDQ1918229

Alan T. K. Wan

Publication date: 5 September 1996

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(95)00110-7

zbMATH Keywords

robustnessmaximum likelihoodleast squaresregression error variancemodel misspecificationminimax regret criterionerror varianceinequality restrictionexact finite sample riskminimum mean squared error component estimatorsoptimal critical valuespreliminary test of an inequality constraint

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Hypothesis testing in multivariate analysis (62H15) Point estimation (62F10) Parametric inference under constraints (62F30)

Related Items (6)

Estimating the error variance after a pre-test for an interval restriction on the coefficients ⋮ A survey on some inequalities for expectation and variance ⋮ Further results on optimal critical values of pre‐test when estimating the regression error variance ⋮ On the sampling performance of an inequality pre-test estimator of the regression error variance under LINEX loss ⋮ Testing inequality constraints in a linear regression model with spherically symmetric disturbances ⋮ Optimal critical values of pre-tests when estimating the regression error variance: Analytical findings under a general loss structure

Uses Software

• NAG
• nag
• BRENT

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
• 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
• 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
• Pre-testing in a mis-specified regression model
• Estimation of the variance in a normal population after the one-sided pre-test for the mean
• On the Use of a Regret Function to Set Significance Points in Prior Tests of Estimation
• Preliminary-test estimation of the regression scale parameter when the loss function is asymmetric
• THE SAMPLING PERFORMANCE OF INEQUALITY RESTRICTED AND PRE‐TEST ESTIMATORS IN A MIS‐SPECIFIED LINEAR MODEL
• THE OPTIMAL CRITICAL VALUE OF A PRE‐TEST FOR AN INEQUALITY RESTRICTION IN A MIS‐SPECIFIED REGRESSION MODEL
• Use of a Preliminary Test in the Estimation of Factorial Means¹
• Risk comparison of the inequality constrained least squares and other related estimators under balanced loss

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