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.
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Publication Date
Sun May 21 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Volume
23
Issue Number
3
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Bayesian Analyses of Ridge Regression Prooblems
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