Implementing WLS requires determining appropriate weights for each data point. A common approach is to use the inverse of the variance of each observation as the weight. This means that observations with higher variance receive less weight, while those with lower variance have more influence on the regression model. The calculation involves estimating the variance for each observation, which can be done using methods like residual analysis from an initial OLS fit or based on prior knowledge about the experimental design.
