This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 403
Type: Topic Contributed
Date/Time: Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #307570
Title: Functional Clustering in Nested Designs
Author(s): Abel Rodriguez*+ and David Dunson
Companies: University of California, Santa Cruz and Duke University
Address: 1156 High Street, Santa Cruz, CA, 95060, USA
Keywords: Nonparametric Bayes ; Nested Dirichlet Process ; Hierarchical Functional Data ; Functional Clustering ; Hormone Profile
Abstract:

We discuss functional clustering procedures for nested designs, where multiple curves are collected for each subject in the study. We start by considering the application of standard functional clustering tools to this problem, which leads to groupings based on the average subject profiles. After discussing some of the shortcomings of this approach, we present a mixture model based on a generalization of the nested Dirichlet process that clusters subjects based on the distribution of their curves. This generalization of the Dirichlet processes induces a more flexible prior on the partitions of the data than other popular model-based clustering methods, allowing for different rates of introduction of new clusters as the number of observations increases. The methods are illustrated using hormone profiles from multiple menstrual cycles collected for women in the Early Pregnancy Study.


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