NDLI: Equality of OLS and Aitken Estimators

Content Provider	Springer Nature Link
Author	Belov, A. G.
Copyright Year	2016
Abstract	We investigate the properties of multiple linear regression estimators obtained by the Ordinary Least Squares method (OLS) and the Generalized Least Squares method (GLS, Aitken estimator) assuming substantially different errors in input data. We illustrate the mechanism that leads to fallacious conclusions about the quality of OLS and Aitken estimators based on visual graphical analysis of experimental data. Numerical simulation and comparative analysis of the estimators is carried out for simple and parabolic regression models.
Starting Page	74
Ending Page	77
Page Count	4
File Format	PDF
ISSN	1046283X
Journal	Computational Mathematics and Modeling
Volume Number	28
Issue Number	1
e-ISSN	1573837X
Language	English
Publisher	Springer US
Publisher Date	2016-12-19
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	OLS estimator Aitken estimator GLS estimator linear regression Mathematical Modeling and Industrial Mathematics Computational Mathematics and Numerical Analysis Applications of Mathematics Optimization
Content Type	Text
Resource Type	Article
Subject	Computational Mathematics

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Equality of OLS and Aitken Estimators