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Activity Number:
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457
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #304368 |
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Title:
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Multilevel Functional Clustering
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Author(s):
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Abel Rodriguez*+
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Companies:
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University of California, Santa Cruz
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Address:
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1156 High Street, Mailstop SOE2, Santa Cruz, CA, 95064,
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Keywords:
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Bayes nonparametric ; Functional data analysis ; Nested Dirichlet Process ; Basis representations
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Abstract:
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This talk discusses clustering procedures for nested samples of curves, where multiple profiles are collected for each subject in the study. We start by considering the application of standard functional clustering tools to this problems, which lead to groupings based on the average profile for each subject. After discussing some of the shortcoming of this approach, we present a model based on a generalization of the nested Dirichlet processes that uses the information on the distribution of curves to generate the clusters. The method is illustrated using data from the Early Pregnancy Study on hormone profiles along multiple menstrual periods for a cohort of women. The resulting model simultaneous clusters both curves and subjects, allowing us to identify outlier curves for each group of women, as well as outlying women whose distribution of profiles differs from the rest.
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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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