The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Abstract Details
Activity Number:
|
26
|
Type:
|
Contributed
|
Date/Time:
|
Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Section on Bayesian Statistical Science
|
Abstract - #301800 |
Title:
|
Spectral Analysis of Variance Models: A Bayesian Nonparametric Approach
|
Author(s):
|
Christian Macaro*+ and Raquel Prado
|
Companies:
|
SAS Institute Inc. and University of California at Santa Cruz
|
Address:
|
1028 oberlin rd, raleigh, NC, 27605,
|
Keywords:
|
Spectral analysis of variance ;
Bayesian nonparametrics ;
Whittle's approximation ;
Bernstein-Dirichlet priors
|
Abstract:
|
The factorial analysis of variance models in the frequency domain is considered. Specifically, the Whittle's approximation to the likelihood function and a Bayesian nonparametric approach provide posterior inference based on Bernstein-Dirichlet prior distributions. The prior is strategically important as it carries identifiability conditions for the models and quantifies the degree of confidence in such conditions. A MCMC Metropolis-Hastings algorithm for posterior inference is presented. The approach is illustrated by analyzing simulated and real data. In particular, a functional magnetic resonance (fMRI) brain analysis is presented where responses are measured in individuals who participated in a designed experiment.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2011 program
|
2011 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.