The exact density and distribution functions of the inequality constrained and pre-test estimators

DOI10.1007/BF02925272zbMath0893.62072MaRDI QIDQ1381204

Alan T. K. Wan

Publication date: 27 April 1998

Published in: Statistical Papers (Search for Journal in Brave)

zbMATH Keywords

pre-test estimatorsbivariate normal linear regression modelinequality restriction

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Exact distribution theory in statistics (62E15)

Related Items (5)

A note on the properties of Stein-rule and inequality restricted estimators when the regression model is over-fitted ⋮ Estimating the error variance after a pre-test for an interval restriction on the coefficients ⋮ Comparisons of estimators for regression coefficient in a misspecified linear model with elliptically contoured errors ⋮ 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

Uses Software

• NAG
• nag

Cites Work

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• On the use of preliminary tests in certain statistical procedures
• The exact distribution of a least squares regression coefficient estimator after a preliminary \(t\)-test
• The density function and the MSE dominance of the pre-test estimator in a heteroscedastic linear regression model with omitted variables
• The exact distribution and density functions of a pre-test estimator of the error variance in a linear regression model with proxy variables
• Estimation of means on the basis of preliminary tests of significance
• Sampling Performance of Some Joint One-Sided Preliminary Test Estimators under Squared Error Loss
• 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
• Risk comparison of the inequality constrained least squares and other related estimators under balanced loss

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