JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 607
Type: Contributed
Date/Time: Thursday, August 7, 2014 : 8:30 AM to 10:20 AM
Sponsor: Business and Economic Statistics Section
Abstract #313497 View Presentation
Title: Spatio-Temporal Modeling and Spatial Clustering of Curves: A Bayesian Approach Applied to Portuguese Regional Fertility Rates
Author(s): Arnab Bhattacharjee*+ and Tapabrata Maiti and Eduardo Castro and Zhen Zhang
Companies: Heriot-Watt University and Michigan State University and Aveiro University and Michigan State University
Keywords: Spatio-temporal modeling ; Conditional Autoregressive model ; Spatial clustering ; Wavelet Smoothing ; Functional mixed-effects model ; Bayesian Hierarchical Model

It is important for social analyses and policy-making to obtain accurate estimates of demographic variables such as age-specific fertility rates, by regions and over time, and the uncertainty associated with such estimation. In this paper, we consider a Bayesian hierarchical model with separable spatio-temporal dependence structure that admits the Markov property and can be estimated by borrowing strength from all regions and years. Further, we explore the local similarity of temporal evolution and dependence by developing a spatial clustering model for temporal or functional data based on Bayesian nonparametric smoothing techniques, such as wavelet shrinkage methods. We extend existing functional mixed-effects model with random block decomposition of the covariance matrix and further, our model allows difference scaling and shrinkage levels of wavelet coefficients across random groups. The traditional empirical Bayes estimators for the hyper-parameters under such random group structure are generally not available, and we derive an empirical procedure to determine a prior distribution to incorporate these parameters in a Gibbs circle. The proposed model is applied to 16-year data o

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.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.