I am trying to build a least-squares regression model and when I analyzed the independent variables, I saw a case of heteroscedasticity in one of the independent variables.
I'm building this model in python and I've thought of using weighted linear least squares instead of ordinary least squares regression. However, because I have more than 1 explanatory variable and statsmodel WLS works for 1 variable, I couldn't find a healthy way to implement it. Then, I tried to transform the data using log-transformation and square root and cubic root transformation, but most of the data is centered around 0. Therefore, these transformations were not helpful in my case as well.
so I was wondering what else I can try and what would work.