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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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