Weighted least squares

Summary

Weighted least squares fits a regression model by minimising a sum of squared residuals in which each observation has its own positive weight. It is the case of generalized least squares in which the errors are uncorrelated but heteroscedastic. With weights inversely proportional to the error variances, it gives the best linear unbiased estimator. It is also the inner step of iteratively reweighted least squares, used to fit generalized linear models and robust regressions.