Robust-biased estimators
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Abstract (EN)
In multiple linear regression analysis, the presence of multicollinearity among explanatory variables and outliers in the y-direction in the datasets affect the ordinary least squares estimator, adversely and lead to unreliable results. In this case, it is suggested to use robust-biased estimators. In this study, new biased estimators based on M-estimator are proposed to overcome the problem of multicollinearity and outliers in the y-direction, simultaneously. The performances of newly proposed estimators are compared theoretically or with simulation study, according to mean square error criterion. Moreover, a numerical example is given to support the results of theoretical comparisons or simulation study.
Author
Hasan Ertaş
How to Cite
Hasan Ertaş (Doctorate thesis). Robust-biased estimators, 2015, Çukurova University.
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