a statistical procedure that generalizes and combines features from principal components analysis and multiple regression. It is used when a researcher wants to estimate the outcomes on a set of dependent variables from a (very) large set of predictors, especially when these predictors have a high degree of multicollinearity or exceed the number of obtained observations.