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Robust Estimator to Deal with Regression Models Having both Continuous and Categorical Regressors: A Simulation Study
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نویسنده
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Talib Bashar A. ,Midi Habshah
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منبع
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malaysian journal of mathematical sciences - 2009 - دوره : 3 - شماره : 2 - صفحه:161 -181
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چکیده
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The ordinary least squares (ols) method has been the most popular technique for estimating the parameters of the multiple linear regression. however, in the presence of outliers and when the model includes both continuous and categorical (factor) variables, the ols can result in poor estimates. in this paper we try to introduce an alternative robust method for such a model that is much less influenced by the presence of outliers.
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کلیدواژه
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Outliers ,Leverage points ,Robust Distance ,S/M-estimates ,RLSRDL1 ,RLSRDSM
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آدرس
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Universiti Putra Malaysia, Faculty of Science, Department of Mathematics, Malaysia, Universiti Putra Malaysia, Faculty of Science, Department of Mathematics, Malaysia. Universiti Putra Malaysia, Institute for Mathematical Research (INSPEM), Laboratory of Applied and Computational Statistics, Malaysia
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پست الکترونیکی
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habshah@putra.upm.edu.my
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Authors
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