This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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52
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Type:
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Invited
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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 Statistical Computing
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| Abstract - #306264 |
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Title:
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Wavelet-Based Functional Linear Regression
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Author(s):
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Yihong Zhao* and Todd Ogden+
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Companies:
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Columbia University and Columbia University
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Address:
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Dept. of Biostatistics, New York, NY, 10032,
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Keywords:
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dimension reduction ;
LASSO ;
variable selection
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Abstract:
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We introduce an approach for estimating the coefficient function in the functional linear model with scalar responses and functional predictors (e.g., curves, spectra, or images). The problem is transformed to a variable selection problem by transformation into the wavelet domain, taking advantage of the sparse representation allowed by wavelet bases. When the number of measurement points is much larger than the number of samples, we reduce the dimensionality by applying a pre-screening step followed by a variable selection step (e.g., penalized least squares).
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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