Linear Regression Functions with Neglected Variables
作者:
HowardL. Jones,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1946)
卷期:
Volume 41,
issue 235
页码: 356-369
ISSN:0162-1459
年代: 1946
DOI:10.1080/01621459.1946.10501881
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
This article discusses some properties of the computedYvalues obtained by fitting a linear regression function to independent observations by the method of least squares. For the general case where the form of the fitted function may not be correct it is proved that (a) the sampling variance of the computed values and of the residual differences is the same as for the special case where the form of the fitted function is correct, and (b) the mean square bias of the set of computed values is less than, or equal to, that of any other set of linear estimates. These and other properties lead to the suggestion that in minimizing the mean square error, one or more variables be neglected unless Snedecor'sFis greater than two.
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