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This is the preliminary program for the 2007 Joint Statistical Meetings in Salt Lake City, Utah.

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Activity Number: 17
Type: Topic Contributed
Date/Time: Sunday, July 29, 2007 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #309158
Title: A Novel Moment-Based Sufficient Dimension Reduction Approach in Multivariate Regression
Author(s): Jae Keun Yoo*+
Companies: University of Louisville
Address: 555 South Floyd Street, Louisville, KY, 40202,
Keywords: sufficient dimension reduction ; multivariate regression ; moment-based method ; predictor tests
Abstract:

Recently, a moment based dimension reduction methodology in multivariate regression, focusing on the first two moments, was introduced. We present in this paper a novel approach of the earlier method. This novel method possesses several desirable properties that the earlier method did not have such as dimension tests with chi-squared distributions, predictor effects test for the first two conditional moments without assuming any model, and so on. Simulated and real data examples are presented for studying various properties of the proposed method and for a numerical comparison of the presented method to the earlier method.

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Revised September, 2007