- Gazi University Journal of Science
- Vol: 30 Issue: 4
- A REVIEW ON SHRINKAGE PARAMETERS IN RIDGE REGRESSION
A REVIEW ON SHRINKAGE PARAMETERS IN RIDGE REGRESSION
Authors : Esra Gökpınar, Meral Ebegil, Fikri Gökpınar
Pages : 565-582
View : 19 | Download : 7
Publication Date : 2017-12-11
Article Type : Other
Abstract :In the regression analysis, it is desired that no multicollinearity between the independent (explanatory) variables exists. In the cases where this is not achieved, the use of Least Square (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