This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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76
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #307884 |
Title:
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Dimension Reduction with Categorical Predictors via Likelihood Approach
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Author(s):
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Xuerong Wen*+
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Companies:
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Missouri University of Science and Technology
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Address:
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400 W. 12th St. , Rolla, MO, 65401, USA
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Keywords:
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sufficient dimension reduction ;
categorical predictors ;
likelihood approach
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Abstract:
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Within the context of sufficient dimension reduction (Cook, 1994), Cook and Forzani (2008) recently proposed a method called LAD (likelihood acquired directions) assuming that given a scalar response, the p-dimensional predictor X follows a normal distribution. We extend LAD to incorporate categorical predictor W. The likelihood approach also enables us to test group effects (whether same directions are required across W) via a likelihood ratio test.
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Authors who are presenting talks have a * after their name.
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