This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
|
422
|
Type:
|
Contributed
|
Date/Time:
|
Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
|
Sponsor:
|
SSC
|
Abstract - #307166 |
Title:
|
Nonparametric State Space Models for Longitudinal Data
|
Author(s):
|
Peter Song and Daimin Shi*+
|
Companies:
|
University of Michigan and Southwestern University of Finance and Economics
|
Address:
|
School of Statistics, Chengdu, International, 610074, China
|
Keywords:
|
Estimating equation ;
Kalman smoother ;
longitudinal data ;
state space model
|
Abstract:
|
We will present a class of nonparametric state space models for the analysis of non-normal longitudinal data, in which the latent process follows a stationary first-order Markov model with exponential dispersion model margins. We propose to use the local linear fitting approach to estimating nonparametric functions through Jorgensen and Song's (2007) Kalman estimating equation. We illustrate the proposed approach via both simulated and real world data examples.
|
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 2010 program
|
2010 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.