Bayesian analyses of ridge regression prooblems

الملخص EN

A Bayesian formulation of the ridge regression problem is considerd, which derives from a direct specification of prior informations about parameters 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.