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Preliminary-Test Estimation of the Error Variance in Linear Regression

dc.contributor.author Clarke, Judith A
dc.contributor.author Giles, David EA
dc.contributor.author Wallace, Dudley
dc.date.accessioned 2010-06-28T18:50:29Z
dc.date.available 2010-06-28T18:50:29Z
dc.date.issued 1987-08
dc.identifier.uri https://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.
dc.format.extent 188317 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.publisher Econometric Theory
dc.subject biases
dc.subject error
dc.subject linear regression
dc.subject pretest estimators
dc.title Preliminary-Test Estimation of the Error Variance in Linear Regression
dc.type Journal article


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