Choosing Ridge Parameter for Regression Problems

Abstract

ABSTRACT Hoerl and Kennard (1970a Hoerl , A. E. , Kennard , R. W. ( 1970a ). Ridge regression: biased estimation for non-orthogonal problems . Tech. 12 : 55 – 67 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) introduced the ridge regression estimator as an alternative to the ordinary least squares estimator in the presence of multicollinearity. In this article, a new approach for choosing the ridge parameter (K), when multicollinearity among the columns of the design matrix exists, is suggested and evaluated by simulation techniques, in terms of mean squared errors (MSE). A number of factors that may affect the properties of these methods have been varied. The MSE from this approach has shown to be smaller than using Hoerl and Kennard (1970a Hoerl , A. E. , Kennard , R. W. ( 1970a ). Ridge regression: biased estimation for non-orthogonal problems . Tech. 12 : 55 – 67 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) in almost all situations.