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:
|
317
|
|
Type:
|
Invited
|
|
Date/Time:
|
Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Business and Economic Statistics Section
|
| Abstract - #300083 |
|
Title:
|
Forecasting Periodic Discrete-Valued Time Series
|
|
Author(s):
|
David S. Matteson*+
|
|
Companies:
|
Cornell University
|
|
Address:
|
282 Rhodes Hall, Ithaca, NY, 14853, United States
|
|
Keywords:
|
Dynamic factor model ;
Smoothing splines
|
|
Abstract:
|
We introduce a new method for forecasting that combines discrete-valued time series models with a dynamic latent factor structure. The factor structure models the observed non-stationary patterns in periodic data and greatly reduces the number of model parameters. The factor model is combined with stationary discrete-valued time series models to capture the remaining serial dependence in the intensity process. We compare frequentist and Bayesian estimation methods to forecast and conduct inference for applications in staffing and manufacturing.
|
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.