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Analysis of Food Poisoning via Zero Inflation Models
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 Title & Authors
Analysis of Food Poisoning via Zero Inflation Models
Jung, Hwan-Sik; Kim, Byung-Jip; Cho, Sin-Sup; Yeo, In-Kwon;
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 Abstract
Poisson regression and negative binomial regression are usually used to analyze counting data; however, these models are unsuitable for fit zero-inflated data that contain unexpected zero-valued observations. In this paper, we review the zero-inflated regression in which Bernoulli process and the counting process are hierarchically mixed. It is known that zero-inflated regression can efficiently model the over-dispersion problem. Vuong statistic is employed to compare performances of the zero-inflated models with other standard models.
 Keywords
Negative binomial regression;Poisson regression;Vuong statistic;
 Language
Korean
 Cited by
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원인균별 식중독 발생 건수 예측,여인권;

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