Comparison of estimation methods for regression model parametersIn the case of the problem of linear multiplicity and abnormal values
DOI:
https://doi.org/10.33095/jeas.v15i55.1260Keywords:
Comparison of estimation methods for regression model parametersIn the case of the problem of linear multiplicity and abnormal valuesAbstract
A simulation study is used to examine the robustness of some estimators on a multiple linear regression model with problems of multicollinearity and non-normal errors, the Ordinary least Squares (LS) ,Ridge Regression, Ridge Least Absolute Value (RLAV), Weighted Ridge (WRID), MM and a robust ridge regression estimator MM estimator, which denoted as RMM this is the modification of the Ridge regression by incorporating robust MM estimator . finialy, we show that RMM is the best among the other estimators
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