In this paper , we consider the problem of estimating the regression parameters in a multiple linear regression model , when the multicollinearity is present under the assumption of normality , we present two types , empirical Bayes and Bayes . One of them shrinks the least squares (LS) estimator towards the principal component .The second type is a hierarchical Bayesian model . A simulation example is given .
Faiz Al-Sadoun,M . (2005). Empirical Bayes and Bayes for Ridge regression. AL-Qadisiyah Journal For Administrative and Economic sciences, 6(1), 169-182.
MLA
Faiz Al-Sadoun,M . "Empirical Bayes and Bayes for Ridge regression", AL-Qadisiyah Journal For Administrative and Economic sciences, 6, 1, 2005, 169-182.
HARVARD
Faiz Al-Sadoun M. (2005). 'Empirical Bayes and Bayes for Ridge regression', AL-Qadisiyah Journal For Administrative and Economic sciences, 6(1), pp. 169-182.
CHICAGO
M Faiz Al-Sadoun, "Empirical Bayes and Bayes for Ridge regression," AL-Qadisiyah Journal For Administrative and Economic sciences, 6 1 (2005): 169-182,
VANCOUVER
Faiz Al-Sadoun M. Empirical Bayes and Bayes for Ridge regression. AL-Qadisiyah Journal For Administrative and Economic sciences. 2005;6(1):169-182.
