EVALUATION AND COMPARISON OF ROBUST ESTIMATORS IN REGRESSION MODELS
MUTHUKRISHNAN.R and M.RADHA.
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.
Robust estimator, M-, L- and R-estimator, scale and location parameter,
asymptotic representation, R software
Youssef, Ahmed H,email@example.com
READING THE ARTICLE: You can read the article in
portable document (.pdf) format (196689 bytes.)
NOTE: The content of this article is the intellectual property of the authors, who retains all rights to future publication.
This page has been accessed 1709 times since MAY 7, 2010.
Return to the Home Page.