This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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306
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #308181 |
Title:
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TreeMARS Models for Use in Stochastic Dynamic Programming Framework
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Author(s):
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Subrat Sahu*+ and Victoria Chen and Seoung Bum Kim
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Companies:
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The University of Texas at Arlington and The University of Texas at Arlington and Korea University
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Address:
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Industrial & Manufacturing Systems Engineering, Arlington, TX, 76019,
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Keywords:
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Regression Splines ;
Regression Trees ;
Statistical Modeling ;
Value Function Approximation ;
Stochastic Dynamic Programming ;
TreeMARS Models
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Abstract:
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Seeking to develop a flexible, nonparametric statistical modeling method which can capture complex non-linearity in data comprised of a mix of quantitative and qualitative variables and can be used to approximate future value functions and to estimate state transition functions in stochastic dynamic programming (SDP) problems with a mix of continuous and categorical state variables, we present a tree-MARS model that first fits a regression tree model, and then uses multivariate adaptive regression splines (MARS) to refine the model at the terminal nodes of the tree. Comparisons are made to the tree-regression model which uses a similar concept, but only permits the use of linear regression at the terminal nodes.
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