JSM 2005 Online Program

Abstract #302959

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page

Legend:

= Applied Session,

= Theme Session,

= Presenter

Activity Number:	486
Type:	Contributed
Date/Time:	Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor:	Section on Nonparametric Statistics
Abstract - #302959
Title:	Affine Equivariant Rank-based and Generalized Rank Estimators for Multivariate Linear Models
Author(s):	Majeda Salman*+ and Joe McKean
Companies:	University of Bahrain and Western Michigan University
Address:	Department of Mathematics, Isa Town, POBox32038, Bahrain
Keywords:	R-estimators ; GR-estimators ; Least squares ; Regression ; Robust ; Efficiency
Abstract:	Affine equivariant estimates for the regression coefficient matrix of the multivariate linear model are proposed. These estimates are based on a transformation and retransformation technique that uses Tyler's (1987) M-estimator of scatter. The proposed estimates are obtained by retransforming the componentwise rank-based estimate due to Davis and McKean (1993) and a componentwise generalized rank estimate. Asymptotic properties of the estimates are established under regularity conditions. It is shown that both estimates have a multivariate normal limiting distribution. The influence function of the retransformed generalized rank estimate has a bounded influence in both factor and response spaces. It is shown through a simulation study that the transformed-retransformed R and GR estimates are highly efficient compared to the nonequivariant componentwise R, GR, and least-absolute deviations estimates. Also, it is shown that the new estimates perform better than the least squares estimate when the errors have a heavy-tailed distribution. Examples illustrating the estimation procedures are presented.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2005 program