JSM 2005 Online Program

Abstract #303959

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.

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Activity Number:	491
Type:	Contributed
Date/Time:	Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor:	Section on Statistical Graphics
Abstract - #303959
Title:	Regression Graphics and Dimension Reduction in Exponential Family
Author(s):	Siamak Noorbaloochi*+ and David B. Nelson
Companies:	VA HSR/University of Minnesota and VA HSR/University of Minnesota
Address:	Minneapolis Medical Center, Minneapolis, MN, 55417, United States
Keywords:	Regression Graphics ; Exponential Family ; Sufficient Summary
Abstract:	We consider informative dimension reduction for Regression Graphics when the response variable takes values in a finite set. For the corresponding inverse regression problem, we assume the distribution of the covariates, given the value for the response variable, is a member of an exponential family. We propose a general dimension reduction technique where the set of predictors is reduced, possibly in a nonlinear fashion, to a smaller number of sufficient summary variables with approximately the same conditional distribution. We apply the methodology to different members of the family. The corresponding estimation procedures for constructing sufficient summaries of minimum dimension are introduced and a test of dimensionality is developed. Finally, the relationship of the underlying theory with other existing theories is discussed.

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