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Statistical Papers

, Volume 39, Issue 1, pp 109–118 | Cite as

Bayesian estimation of the linear regression model with an uncertain interval constraint on coefficients

  • Alan T. K. Wan
  • William E. Griffiths
Notes

Abstract

This article considers Bayesian inference in the interval constrained normal linear regression model. Whereas much of the previous literature has concentrated on the case where the prior constraint is correctly specified, our framework explicitly allows for the possibility of an invalid constraint. We adopt a non-informative prior and uncertainty concerning the interval restriction is represented by two prior odds ratios. The sampling theoretic risk of the resulting Bayesian interval pre-test estimator is derived, illustrated and explored.

Keywords

Linear Regression Model Inequality Constraint Risk Function Prior Constraint Sampling Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 1998

Authors and Affiliations

  • Alan T. K. Wan
    • 1
  • William E. Griffiths
    • 2
  1. 1.Department of Applied Statistics and Operational ResearchCity University of Hong KongKowloonHong Kong
  2. 2.Department of EconometricsUniversity of New EnglandArmidaleAustralia

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