Abstract #301613

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JSM 2003 Abstract #301613
Activity Number: 54
Type: Contributed
Date/Time: Sunday, August 3, 2003 : 4:00 PM to 5:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #301613
Title: Rank Estimation of Regression Coefficients Using Iterated Reweighted Least Squares
Author(s): Asheber Abebe*+
Companies: Auburn University
Address: Discrete & Statistical Sciences, Auburn, AL, 36849-0001,
Keywords: Wilcoxon ; R-estimate ; RGLM ; score function ; linear models
Abstract:

This talk is concerned with the rank estimator for the slope parameter vector in a linear model which is obtained by the minimization of a rank dispersion function. The rank estimator has many advantages over the regular least squares estimator, but the inaccessibility of software to carry out its computation has limited its use. An iterated reweighted least squares algorithm is presented for the computation of the rank estimator. The method is simple in concept and can be carried out readily with a wide variety of statistical software. Details of the method are discussed along with some results on its asymptotic distribution and numerical stability. Some examples are presented to show advantages of the rank method.

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