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The asymptotic behaviour of the estimated generalized least squares method in the linear regression model
Author(s) -
Genugten B.B. Van Der
Publication year - 1983
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.1983.tb00807.x
Subject(s) - mathematics , generalized least squares , total least squares , generalized linear model , covariance matrix , least squares function approximation , estimator , linear regression , statistics , linear model , iteratively reweighted least squares , design matrix , partial least squares regression , regression analysis
In the linear regression model the generalized least squares (GLS) method is only applicable if the covariance matrix of the errors is known but for a scalar factor. Otherwise an estimator for this matrix has to be used. Then we speak of the estimated generalized least squares (EGLS) method. In this paper the asymptotic behaviour of both methods is compared. Results are applied to some standard models commonly used in econometrics