Algorithm for the L1-Regression Estimation with High Breakdown Point

Title & Authors
Algorithm for the L1-Regression Estimation with High Breakdown Point
Kim, Bu-Yong;

Abstract
The $\small{L_1}$-regression estimator is susceptible to the leverage points, even though it is highly robust to the vertical outliers. This article is concerned with the improvement of robustness of the $\small{L_1}$-estimator. To improve its robustness, in terms of the breakdown point, we attempt to dampen the influence of the leverage points by means of reducing the weights corresponding to the leverage points. In addition the algorithm employs the linear scaling transformation technique, for higher computational efficiency with the large data sets, to solve the linear programming problem of $\small{L_1}$-estimation. Monte Carlo simulation results indicate that the proposed algorithm yields $\small{L_1}$-estimates which are robust to the leverage points as well as the vertical outliers.
Keywords
$\small{L_1}$-estimation;vertical outlier;leverage point;robustness;breakdown point;
Language
Korean
Cited by
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