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dc.contributor.author Clarke, Judith A. en_US
dc.contributor.author Giles, David E. A. en_US
dc.contributor.author Wallace, Dudley en_US
dc.date.accessioned 2010-06-28T18:50:29Z
dc.date.available 2010-06-28T18:50:29Z
dc.date.issued 1987-08 en_US
dc.identifier.uri http://hdl.handle.net/10161/2568
dc.description.abstract We derive exact finite-sample expressions for the biases and risks of several common pretest estimators of the scale parameter in the linear regression model. These estimators are associated with least squares, maximum likelihood and minimum mean squared error component estimators. Of these three criteria, the last is found to be superior (in terms of risk under quadratic loss) when pretesting in typical situations. en_US
dc.format.extent 188317 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.publisher Econometric Theory en_US
dc.subject biases en_US
dc.subject error en_US
dc.subject linear regression en_US
dc.subject pretest estimators en_US
dc.title Preliminary-Test Estimation of the Error Variance in Linear Regression en_US
dc.type Journal Article en_US
dc.department Economics

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