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Abstract Details
Activity Number:
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451
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Learning and Data Mining
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Abstract - #300722 |
Title:
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Robust Functional Singular Value Decomposition Method
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Author(s):
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Lingsong Zhang*+
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Companies:
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Purdue University
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Address:
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150 N. University St, West Lafayette, IN, 47907, United States
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Keywords:
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functional data analysis ;
smoothing ;
robust method ;
outliers ;
GCV
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Abstract:
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Motivated by the analysis of a two-way functional data, we propose a novel robust functional singular value decomposition method. The regularized part of this method smoothes the estimated singular column and singular row. It also downweights the outlying effects slightly.The robustness part further reduces the outlying effects. A GCV method is developed for the smoothing parameter selection. Simulations are conducted to illustrate the usefulness of this new method.
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Authors who are presenting talks have a * after their name.
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