Bayesian estimation of the linear regression model with an uncertain interval constraint on coefficients |
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Authors: | Alan T K Wan William E Griffiths |
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Institution: | (1) Department of Applied Statistics and Operational Research, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong;(2) Department of Econometrics, University of New England, 2351 Armidale, N. S. W., Australia |
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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.
The authors are grateful to the editor and the referee for their helpful comments. |
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Keywords: | |
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