Abstract #300338

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JSM 2003 Abstract #300338
Activity Number: 89
Type: Contributed
Date/Time: Monday, August 4, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #300338
Title: Tree-Augmented Regression Analysis
Author(s): Xiaogang Su*+ and Chung-Ching Morgan Wang and Chih-Ling Tsai
Companies: University of Central Florida and University of Central Florida and University of California
Address: Department of Statistics, Orlando, FL, 32816-0001,
Keywords: interaction ; linear regression model ; regression trees ; transition model
Abstract:

This paper introduces the TAR algorithm, which augments the linear regression model with a tree structure. The proposed method can be described as a "father regression and mother tree" idea, not only capturing global patterns of data structure, but also identifying local properties at finer levels. As a result it yields better predictions without loss of interpretability, and moreover, its flexibility makes it a useful routine procedure for data analysis. We illustrate the use of the TAR model by assessing treatment effects in the presence of confounding covariates, detecting interactions in an explicit manner, and estimating transitions with unknown number of change points. A real data application of TAR analyzing baseball salary data is also presented.

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