Model with AR(1) Error: A Comparative Simulation Study
The performance of shrinkage ridge estimators in the linear regression model has been studied to reduce the effect of multicollinearity on the estimation of the linear regression parameters. Trenkler (1984) proposed a ridge estimator in the linear regression model when the assumption of uncorrelatedness is not satisfied. Since there is no attempt to study the recent types of estimated ridge parameter when the assumption of uncorrelatedness is not satisfied, this paper tries to show the performance of some ridge estimators in the linear regression model with correlated error based on the minimum mean squared error (MSE) criterion. A simulation study and a numerical example have been made to evaluate the performance of these estimators of ridge parameter k. The simulation study suggests that some ridge estimators are promising and can be recommenced for the practitioners.
Linear Model; Multicollinearity; MSE; Ridge Regression; Simulation Study.
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