How To Apply Generalized Least Squares Regressions To Draw Conclusions. And so we are under the assumptions of ordinary least squares. 4 classical measures of performance 4.1 bias 4.2 variances 4.2.1 the variance of ols 4.2.2 the variance of gls 4.2.3 a remark on the variances 4.3 confidence intervals 4.3.1 a remark on the critical values

(x0v −1x)β = xv −1y normal equations the generalized least squares estimator of β is 1 generalized least squares in the standard linear model (for example, in chapter 4 of the r companion), e(yjx) = x or, equivalently y = x + X [e [b | x]] = β.