Weighted Ridge MM-Estimator in Robust Ridge Regression with Multicollinearity
نویسندگان
چکیده
This study is about the development of a robust ridge regression estimator. It is based on weighted ridge MM-estimator (WRMM) and is believed to have potentials in remedying the problems of multicollinearity. The proposed method has been compared with several existing estimators, namely ordinary least squares (OLS), robust regression based on MM estimator, ridge regression (RIDGE), weighted ridge (WRID) and ridge MM-estimator (RMM) using two criteria; biasness and root mean square error (RMSE). The efficiency of the proposed method relative to the alternatives has been examined using MSE ratios. In general, it has been found that the proposed estimator scores well against the five existing estimators when the error term is non-normal. Key-Words: multicollinearity; ridge regression; MM-estimator; robust; weighted ridge MM
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