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Best Linear Unbiased Prediction in the Generalized Linear Regression Model

Arthur S. Goldberger
Journal of the American Statistical Association
Vol. 57, No. 298 (Jun., 1962), pp. 369-375
DOI: 10.2307/2281645
Stable URL: http://www.jstor.org/stable/2281645
Page Count: 7
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Best Linear Unbiased Prediction in the Generalized Linear Regression Model
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Abstract

When interdependence of disturbances is present in a regression model, the pattern of sample residuals contains information which is useful in prediction of post-sample drawings. This information, which is often overlooked, is exploited in the best linear unbiased predictor derived here. The gain in efficiency associated with using this predictor instead of the usual expected value estimator may be substantial.

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