A REVIEW ON SHRINKAGE PARAMETERS IN RIDGE REGRESSION

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Gazi University Journal of Science
Volume:30 Issue:4
A REVIEW ON SHRINKAGE PARAMETERS IN RIDGE REGRESSION

A REVIEW ON SHRINKAGE PARAMETERS IN RIDGE REGRESSION

Authors : Esra Gökpınar, Meral EBEGİL, Fikri Gökpınar

Pages : 565-582

View : 25 | Download : 13

Publication Date : 2017-12-11

Article Type : Other Papers

Abstract :In the regression analysis, it is desired that no multicollinearity between the independent insert ignore into journalissuearticles values(explanatory); variables exists. In the cases where this is not achieved, the use of Least Square insert ignore into journalissuearticles values(LS); estimation method leads to mismodelling. Some methods have been developed to solve this problem; one of which is the ‘biased estimation method’. When there exists collinearity, selection of the shrinkage parameter is important. In this study, a test statistics for Ridge estimator that is kind of shrinkage biased estimators was investigated. Also the estimators of shrinkage parameter are compared via simulation.
Keywords : Ridge Estimator, Mean Square Error, Optimum Ridge Parameter

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