On Necessary and Sufficient Conditions for Ordinary Least Squares Estimators to Be Best Linear Unbiased Estimators
- 1 November 1984
- journal article
- research article
- Published by Taylor & Francis in The American Statistician
- Vol. 38 (4) , 298-299
- https://doi.org/10.1080/00031305.1984.10483234
Abstract
Two often-quoted necessary and sufficient conditions for ordinary least squares estimators to be best linear unbiased estimators are described. Another necessary and sufficient condition is described, providing an additional tool for checking to see whether the covariance matrix of a given linear model is such that the ordinary least squares estimator is also the best linear unbiased estimator. The new condition is used to show that one of the two published conditions is only a sufficient condition.Keywords
This publication has 2 references indexed in Scilit:
- An Integral of the Bivariate Normal and an ApplicationThe American Statistician, 1983
- A Necessary and Sufficient Condition That Ordinary Least-Squares Estimators Be Best Linear UnbiasedJournal of the American Statistical Association, 1967