Modeling Spatial-Temporal Epidemics Using STBL Model

Author

Billard, Lynne ; Duck-Ki Kim ; Chan-Hee Lee ; Lee, Keon-Myung ; Lee, Chan-Hee ; Kim, Sung-Soo

Author_Institution

Univ. of Georgia, Athens

fYear

2007

fDate

13-15 Dec. 2007

Firstpage

629

Lastpage

633

Abstract

The Space Time Bilinear (STBL) model is a special form of a multiple bilinear time series which can be used to model time series which exhibit bilinear behavior on a spatial neighborhood structure. The STBL model and its identification have been proposed and discussed by Dai and Billard (1998). In this paper, we compare the STBL model with STARMA and single ARMA model. All problems are addressed by setting up the model in state space form and applying the Kalman filter. An application of the STBL model to epidemic surveillance data is given and the results com pared with those from other models.

Keywords

Kalman filters; autoregressive moving average processes; diseases; state-space methods; time series; Kalman filter; STARMA model; bilinear behavior; epidemic modeling; multiple bilinear time series; single ARMA model; space time bilinear model; spatial neighborhood structure; spatial-temporal epidemics; state space form; Application software; Context modeling; Diseases; Educational institutions; Electric shock; Machine learning; Parameter estimation; Predictive models; Statistics; Surveillance;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Applications, 2007. ICMLA 2007. Sixth International Conference on

Conference_Location

Cincinnati, OH

Print_ISBN

978-0-7695-3069-7

Type

conf

DOI

10.1109/ICMLA.2007.112

Filename

4457300