Generalized Ridge Regression: Applications to Nonorthogonal Linear Regression Models

Abstract

This paper analyzes the possibilities of using the generalized ridge regression to mitigate multicollinearity in a multiple linear regression model. For this purpose, we obtain the expressions for the estimated variance, the coefficient of variation, the coefficient of correlation, the variance inflation factor and the condition number. The results obtained are illustrated with two numerical examples.

25 pages, 7 figures, 12 tables, working paper