Asar, YasinKaraibrahimoglu, AdnanGenc, Asir2020-03-262020-03-2620142651-477Xhttps://hdl.handle.net/20.500.12395/30996In multiple regression analysis, the independent variables should be uncorrelated within each other. If they are highly intercorrelated, this serious problem is called multicollinearity. There are several methods to get rid of this problem and one of the most famous one is the ridge regression. In this paper, we will propose some modified ridge parameters. We will compare our estimators with some estimators proposed earlier according to mean squared error (MSE) criterion. All results are calculated by a Monte Carlo simulation. According to simulation study, our estimators perform better than the others in most of the situations in the sense of MSE.eninfo:eu-repo/semantics/closedAccessMulticollinearitymultiple linear regressionridge regressionridge estimatorMonte Carlo SimulationArticle435827841Q3WOS:000347016500016Q4