Abstract
In this article, an estimation procedure to simple linear regression in the presence of outliers is proposed. The performance of the proposed estimator, the AM estimator, is compared with other traditional estimators: least squares, Theil type repeated median, and geometric mean. A numerical example is given to illustrate the proposed estimator. Simulation results indicate that the proposed estimator is accurate and has a high precision in the presence of outliers.
DOI
10.22237/jmasm/1130804040
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
