|
Activity Number:
|
319
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Tuesday, August 4, 2009 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Section on Statistical Computing
|
| Abstract - #304268 |
|
Title:
|
Efficient Uk's Redescending M-estimator for Robust Regression
|
|
Author(s):
|
Umair Khalil*+ and Fazli Qadir and Amjad Ali
|
|
Companies:
|
University of Peshawar and University of Peshawar and University of Peshawar
|
|
Address:
|
Department of Statistics, Peshawar, International, 25120, Pakistan
|
|
Keywords:
|
Robust Regression ; Outliers ; Leverage Point ; Breakdown Point
|
|
Abstract:
|
M-estimators are used as a robust replacement of the general classical estimators used in the filed of statistics. Redescending M-estimators are those estimators which rejects the extreme values completely. In this paper we present a new "Uk's redescending M-estimator" for robust regression and outlier detection which will provide protection against outliers. Moreover its ?-function is more linear in the central segment before it redescends. Simulation studies shows that Uk's Redescending M-estimator is more efficient than the other estimators. We also have applied the estimator to the real world data taken from the literature. The newly developed Uk's Redescending M-estimator give a general idea to interconnect all the Redescending M-estimators with that of the idea used in Andrews sine function. A couple of which has been solved and the rest are under study for the mathematical solution.
|
