Explicit Equations to Determine the Variances of Regression Coefficients of OLS and GLS Estimators In An Auto-Correlated Regression Models

Samir K Safi

Article Details

Explicit Equations to Determine the Variances of Regression Coefficients of OLS and GLS Estimators In An Auto-Correlated Regression Models

Authors:

Samir K Safi

Publisher:

Islamic University of Gaza

Journal:

IUG Journal of Natural Studies Vol.16 Issue 1, pp.0-0

Document Type:

Article

Publication Date:

2/2015

Document Language:

Arabic

Document ID (Org No.):

2001390118

pISSN:

2790-1653

Abstract:

 We have derived explicit equations to determine the variances of the regression coefficients of ordinary least squares (OLS) and generalized least squares (GLS) estimators in regression models containing an auto-correlated disturbance term for any covariance matrix and design vectors. In addition, we have proved that scaling or shifting the design vector has no effect in the relative efficiency of the variance of GLS to that of OLS. Keywords: Variance; Ordinary Least Squares; Generalized Least Squares; Efficiency.

Article Details

Explicit Equations to Determine the Variances of Regression Coefficients of OLS and GLS Estimators In An Auto-Correlated Regression Models

Authors: Samir K Safi

Publisher: Islamic University of Gaza

Journal: IUG Journal of Natural Studies Vol.16 Issue 1, pp.0-0

Document Type: Article

Publication Date: 2/2015

Document Language: Arabic

Document ID (Org No.): 2001390118

pISSN: 2790-1653

Issues

Authors:

Samir K Safi

Publisher:

Islamic University of Gaza

Journal:

IUG Journal of Natural Studies Vol.16 Issue 1, pp.0-0

Document Type:

Article

Publication Date:

2/2015

Document Language:

Arabic

Document ID (Org No.):

2001390118

pISSN:

2790-1653