WorkshopsDimension Reduction for Functional Data
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Functional data are intrinsically infinite dimensional, so dimension reduction methods are often needed to handle it. The approaches might differ for dense and sparse functional data. In this talk, we'll review some of the approaches, including principal component based methods and dimension reduction regression models.
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Jane Ling Wang
2012-07-24
10:05:00 - 11:10:00
308 , Mathematics Research Center Building (ori. New Math. Bldg.)
Functional data are intrinsically infinite dimensional, so dimension reduction methods are often needed to handle it. The approaches might differ for dense and sparse functional data. In this talk, we'll review some of the approaches, including principal component based methods and dimension reduction regression models.