The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
|
Activity Number:
|
655
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Section on Statistical Computing
|
| Abstract - #306465 |
|
Title:
|
Perfect Sampling in the Dirichlet-Multinomial Hierarchical Model
|
|
Author(s):
|
Nathan Stein*+ and Xiao-Li Meng
|
|
Companies:
|
Harvard University and Harvard University
|
|
Address:
|
Department of Statistics, Cambridge, MA, 02138-2901, United States
|
|
Keywords:
|
Perfect sampling ;
Bounding chain ;
MCMC ;
Data augmentation
|
|
Abstract:
|
This work presents a convenient data augmentation strategy for fitting the hyperparameters of the conjugate Dirichlet-Multinomial hierarchical model. The fact that the augmentation is discrete with a finite state space facilitates perfect sampling from the posterior distribution of the hyperparameters. The algorithm uses a bounding chain that extends perfect sampling methods designed for distributions with an anti-monotonicity structure. The augmentation strategy relies on a non-homogeneous binomial construction closely related to the standard approach in finite mixture models of treating allocation indicators as missing data.
|
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 2012 program
|
2012 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.