Bounded-leverage weights for robust regression estimators |
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Authors: | Dovalee Dorsett |
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Affiliation: | Department of Information Systems , Baylor University , Waco, TX, 76798 |
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Abstract: | Both the least squares estimator and M-estimators of regression coefficients are susceptible to distortion when high leverage points occur among the predictor variables in a multiple linear regression model. In this article a weighting scheme which enables one to bound the leverage values of a weighted matrix of predictor variables is proposed. Bounded-leverage weighting of the predictor variables followed by M-estimation of the regression coefficients is shown to be effective in protecting against distortion due to extreme predictor-variable values, extreme response values, or outlier-induced multieollinearites. Bounded-leverage estimators can also protect against distortion by small groups of high leverage points. |
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Keywords: | influential observations leverage points regression diagonstics |
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