Weighted least squares

This article or section may need to be cleaned up or summarized because it has been split from/to Least squares and Linear least squares (mathematics).

Weighted least squares (WLS), also known as weighted linear regression,^[1][2] is a generalization of ordinary least squares and linear regression in which knowledge of the unequal variance of observations (heteroscedasticity) is incorporated into the regression. WLS is also a specialization of generalized least squares, when all the off-diagonal entries of the covariance matrix of the errors, are null.