JSM 2011 Online Program

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Abstract Details

Activity Number: 451
Type: Topic Contributed
Date/Time: Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #300722
Title: Robust Functional Singular Value Decomposition Method
Author(s): Lingsong Zhang*+
Companies: Purdue University
Address: 150 N. University St, West Lafayette, IN, 47907, United States
Keywords: functional data analysis ; smoothing ; robust method ; outliers ; GCV
Abstract:

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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