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A Necessary and Sufficient Condition that Ordinary Least-Squares Estimators be Best Linear Unbiased
F. W. McElroy
Journal of the American Statistical Association
Vol. 62, No. 320 (Dec., 1967), pp. 1302-1304
Stable URL: http://www.jstor.org/stable/2283779
Page Count: 3
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It is shown that in a standard linear regression model ordinary least-squares estimators are best linear unbiased if and only if the errors have the same variance and the same nonnegative coefficient of correlation between each pair.
Journal of the American Statistical Association © 1967 American Statistical Association