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Activity Number: 110
Type: Contributed
Date/Time: Monday, August 3, 2009 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #304784
Title: The Theil-Sen Estimators in a Multiple Regression Model When Covariates Are Nonrandom
Author(s): Fang Li*+ and Hanxiang Peng
Companies: Indiana University-Purdue University Indianapolis and Indiana University Purdue University Indianapolis
Address: 402 N. Blackford Street, LD270, Indianapolis, IN, 46202,
Keywords: multivariate median ; Theil-Sen estimator ; multiple regression ; robustness ; efficiency
Abstract:

In this article, we propose the Theil-Sen estimators of parameters in a multiple regression model when the covariates are nonrandom using multivariate medians. We show that the proposed estimators are robust, consistent and asymptotically normal under mild conditions. We also investigate the efficiency of the proposed estimators. Simulations are conducted to compare robustness and efficiency with least squares estimators.

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