Abstract Details
Activity Number:
|
221
|
Type:
|
Topic Contributed
|
Date/Time:
|
Monday, August 4, 2014 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Section on Bayesian Statistical Science
|
Abstract #311565
|
|
Title:
|
Joint Clustering and Registration for Functional Data
|
Author(s):
|
Yafeng Zhang*+ and Donatello Telesca and Steve Horvath
|
Companies:
|
Amgen and University of California, Los Angeles and University of California, Los Angeles
|
Keywords:
|
Curve registration ;
Curve clustering ;
Functional data ;
Dirichlet process ;
Nonparametric Bayesian statistics ;
MCMC
|
Abstract:
|
Methods have been proposed for registration and clustering for functional data separately. However, those models are not adequate in some situations where simultaneous curve registration and clustering are necessary. In this article, we propose a Bayesian hierarchical model for joint curve registration and clustering. With B-spline representations of shape functions and time transformation functions, our model provides flexible nonlinear modeling for both functions; With a Dirichlet process model for clustering, it identifies both cluster numbers and clustering structure among curves. We test the joint model on simulated datasets and show that it performs better than models for clustering only or registration only. We also apply the model to the Berkeley Growth Data and time course expression data of the response of Human fibroblasts to serum stimulation.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.