I am wondering what methods are available for incorporating prior knowledge of some variable that is correlated with the unknown regression coefficients in a ridge regression. I have a sparse matrix with a high level of multicollinearity. I have knowledge of variable which is correlated to my coefficients. However, the known variable ranges strictly 0-8 while the coefficients can vary from around -10 to 10 (without strict bounds). How can this known variable be incorporated into the regression?
I am currently using scikit-learn RidgeCV in Python for the analysis.