Bayesian Analyses of Ridge Regression Prooblems

A Bayesian formulation of the ridge regression problem is considerd, which derives from a direct sp ecification of prior informations about p arameters of general linear regression model when data suffer from a high degree of multicollinearity .A new approach for deriving the conventional estimator for the ridge parameter proposed by Hoerl and Kennard (1970) as well as Bayesian estimator are presented. A numerical example is studied in order to compare the performance of these estimators.