New Estimators of Disturbances in Regression Analysis
作者:
A.P. J. Abrahamse,
J. Koerts,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1971)
卷期:
Volume 66,
issue 333
页码: 71-74
ISSN:0162-1459
年代: 1971
DOI:10.1080/01621459.1971.10482221
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
In this article, an alternative v for the vector û of least-squares residuals in the linear model is derived. It is best in the class of all linear unbiased estimators' of u having a certain fixed covariance matrix chosen a priori. Under the normality assumption, the distribution of the Von Neumann Ratio based on v is independent of the regression vectors, so that v is particularly useful for testing on serial correlation of the disturbances. It is pointed out that the existing tests for serial correlation in economic time-series models might be improved by using v based on an appropriate covariance matrix; the Durbin-Watson upper-bound tables can be used for this purpose.
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