LAD Regression and Nonparametric Methods for Detecting Outliers and Leverage Points
Giuseppe Melfi, Susana Faria
Abstract
The detection of influential observations for the standard least squares regression model is a question that has been extensively studied. LAD regression diagnostics offers alternative approaches whose main feature is the robustness. In this paper a new approach for nonparametric detection of influencial observations in LAD regression models is presented and compared with other classical methods of diagnostics.
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