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http://dx.doi.org/10.7465/jkdi.2012.23.6.1117

Models for forecasting food poisoning occurrences  

Yeo, In-Kwon (Department of Statistics, Sookmyung Women's University)
Publication Information
Journal of the Korean Data and Information Science Society / v.23, no.6, 2012 , pp. 1117-1125 More about this Journal
Abstract
The occurrence of food poisoning is usually modeled by meteorological variables like the temperature and the humidity. In this paper, we investigate the relationship between food poisoning occurrence and climate variables in Korea and compare Poisson regression and autoregressive moving average model to select the forecast model. We confirm that lagged climate variables affect the food poisoning occurrences. However, it turns out that, from the viewpoint of the prediction, the number of previous occurrences is more influential to the current occurrence than meteorological variables and Poisson regression model is less reliable.
Keywords
Autoregressive moving average model; cross correlation; Poisson regression model;
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Times Cited By KSCI : 6  (Citation Analysis)
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