基于STBL模型的时空流行病建模

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI:10.1109/ICMLA.2007.112

L. Billard, Duck-Ki Kim, Chan-Hee Lee, Sung Duck Lee, Keon-Myung Lee, Sung-Soo Kim

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引用次数: 4

摘要

时空双线性(STBL)模型是多重双线性时间序列的一种特殊形式，可用于对空间邻域结构上表现双线性行为的时间序列进行建模。Dai和Billard(1998)提出并讨论了STBL模型及其识别。本文将STBL模型与STARMA和单ARMA模型进行了比较。通过状态空间模型的建立和卡尔曼滤波的应用，解决了这些问题。给出了STBL模型在传染病监测数据中的应用，并与其他模型的结果进行了比较。

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Modeling Spatial-Temporal Epidemics Using STBL Model

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.

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Sixth International Conference on Machine Learning and Applications (ICMLA 2007)

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