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Detection of outliers in weighted least squares regression
Authors:Bang Yong Sohn  Guk Boh Kim
Institution:1. Department of Computer Engineering, Daejin University, 487-800, Kyunggi-Do, Korea
Abstract:In multiple linear regression model, we have presupposed assumptions (independence, normality, variance homogeneity and so on) on error term. When case weights are given because of variance heterogeneity, we can estimate efficiently regression parameter using weighted least squares estimator. Unfortunately, this estimator is sensitive to outliers like ordinary least squares estimator. Thus, in this paper, we proposed some statistics for detection of outliers in weighted least squares regression.
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