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SEMINAR DETAILS
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Time: |
2:00 PM - 3:00 PM
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Place: |
133 Rosenau Hall Auditorium
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Speaker: |
Todd Ogden, Ph.D.
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Affiliation |
Department of Biostatistics
Columbia University
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Title & Abstract: |
Regression Models with Signals or Images as Predictors
Regression of a scalar response on functional predictors (or signals), such as spectra or images, presents a major challenge when, as is typically the case, the dimension of the signals far exceeds the number of signals in the dataset. Fitting such a model meaningfully requires some form of dimension reduction. One approach to this problem extends common multivariate methods (principal component regression (PCR) and partial least squares (PLS)) to handle functional data by also incorporating a roughness penalty. This approach will be presented, along with some preliminary work using wavelets for the dimension reduction. These methods are illustrated using data from near infrared (NIR) spectra from chemical samples and data from a brain imaging study. |
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Contact : |
Tania Osborn (919) 966-7268
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Notes: |
n/a |
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Last updated February 13, 2008 |
