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In a linear regression model, it is often assumed that the explanatory variables are independent. This assumption is often violated and Ridge Regression estimator introduced by  has been identified to be more efficient than ordinary least square (OLS) in handling it. However, it requires a ridge parameter, K, of which many have been proposed. In this study, estimators based on Hoerl and Kennard were classified into different forms and various types and some modifications were proposed todoi:10.15672/hjms.201815671 fatcat:oqg7jfo3ujfgdhix5ybb7nvk4u