A Spatial-Temporal ARMA Model of the Incidence of Hand, Foot, and Mouth Disease in Wenzhou, China
To investigate the variability of HFMD in each county of Wenzhou, a spatial-temporal ARMA model is presented, and a general Bayesian framework is given for parameter estimation. The proposed model has two advantages: (i) allowing time series to be correlated, thus it can describe the series both spa...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/238724 |
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| Summary: | To investigate the variability of HFMD in each county of Wenzhou, a spatial-temporal ARMA
model is presented, and a general Bayesian framework is given for parameter estimation. The
proposed model has two advantages: (i) allowing time series to be correlated, thus it can
describe the series both spatially and temporally; (ii) implementing forecast easily. Based on
the HFMD data in Wenzhou, we find that HFMD had positive spatial autocorrelation and
the incidence seasonal peak was between May and July. In the county-level analysis, we find
that after first-order difference the spatial-temporal ARMA (0,0)×(1,0)12 model provides an
adequate fit to the data. |
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| ISSN: | 1085-3375 1687-0409 |