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Abstract Details
Activity Number:
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127
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 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 - #302284 |
Title:
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Functional Sliced Average Variance Estimates
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Author(s):
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Wenting Fan*+ and Yehua Li
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Companies:
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University of Georgia and University of Georgia
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Address:
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The University of Georgia Department of Statistics, Athens, GA, 30602,
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Keywords:
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Functional data analysis ;
Sliced average variance estimates ;
B-Spline
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Abstract:
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We address the problem of extending multivariate dimension reduction methods on functional data analysis. In this paper, Sliced Average Variance Estimates (SAVE) is considered for functional data where the response variable is a scalar and prediction variables are curves. Due to this nature, the estimation procedure of SAVE cannot be directly applied although some properties can be retained. To address this problem, we propose B-Spline estimator for conditional variance on functional data. We demonstrate that on a benchmark classification task for functional data, the classification result based on Support Vector Machine (SVM) with our extended SAVE and a non-linear form classifier achieves the best result, whereas a linear form classifier fails, while also outperforming the methods without dimension reduction.
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