Gls Regression. Feb 14 2016 Explanation. Minimizing the sum of the squares of the differences between the observed dependent variable in the given dataset and those.
Y has the same variance for each x. When the noise is of unequal variance heteroscedasticity. Generalized least squares minimizes y Xb TS 1 y Xb which is solved by b XTS 1X 1XTS 1y Since we can write S SST where S is a triangular matrix using the Choleski Decomposition we have y Xb TS TS 1 y Xb S 1y S 1Xb T S 1y S 1Xb So GLS is like regressing S 1X on S 1y.
OLS Consistency and Asymptotic Normality 8 Stata commands 9 Appendix.
Of Calif- Davis Frontiers in Econometrics. This is a form of weighted least squares. Active 3 years 8 months ago. Generalised least squares GLS is used for heteroscedastic regression different variances.
