Best Linear Unbiased Prediction in the Generalized Linear Regression Model
作者:
ArthurS. Goldberger,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1962)
卷期:
Volume 57,
issue 298
页码: 369-375
ISSN:0162-1459
年代: 1962
DOI:10.1080/01621459.1962.10480665
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
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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