Bayesian Analyses of Ridge Regression Prooblems
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Abstract
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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Bayesian Analyses of Ridge Regression Prooblems. (2017). Ibn AL-Haitham Journal For Pure and Applied Sciences, 23(3), 253-264. https://jih.uobaghdad.edu.iq/index.php/j/article/view/898
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Mathematics
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How to Cite
Bayesian Analyses of Ridge Regression Prooblems. (2017). Ibn AL-Haitham Journal For Pure and Applied Sciences, 23(3), 253-264. https://jih.uobaghdad.edu.iq/index.php/j/article/view/898