EVALUATION AND COMPARISON OF ROBUST ESTIMATORS IN REGRESSION MODELS

by MUTHUKRISHNAN.R and M.RADHA.

Abstract: The theory of robustness developed by Huber and Hampel laid the foundation for finding practical solutions too many problems, when statistical concepts were vague to serve the purpose. Many researchers have worked in this field and described the methods of evaluating the robust estimators. In this paper, an attempt is made to evaluate and compare such methods with the least square estimator. The asymptotic representations and the relations among these estimators along with the applications in regression models are provided. A comparative study of these estimators providing certain numerical illustrations by using R software is carried out.

Key Words: Robust estimator, M-, L- and R-estimator, scale and location parameter, asymptotic representation, R software

Authors:
M.Radha, radhamyilsamy@gmail.com
R.Muthukrishnan, muthukrishnan70@rediffmail.com

Editor: Youssef, Ahmed H,ahyoussef@hotmail.com

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