LAD Regression and Nonparametric Methods for Detecting Outliers and Leverage Points
Statistics Theory
2014-10-03 v1 Statistics Theory
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.
Cite
@article{arxiv.math/0507510,
title = {LAD Regression and Nonparametric Methods for Detecting Outliers and Leverage Points},
author = {Giuseppe Melfi and Susana Faria},
journal= {arXiv preprint arXiv:math/0507510},
year = {2014}
}