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http://dx.doi.org/10.5351/KJAS.2012.25.5.859

Analysis of Food Poisoning via Zero Inflation Models  

Jung, Hwan-Sik (Department of Statistics, Seoul National University)
Kim, Byung-Jip (Department of Statistics, Seoul National University)
Cho, Sin-Sup (Department of Statistics, Seoul National University)
Yeo, In-Kwon (Department of Statistics, Sookmyung Women's University)
Publication Information
The Korean Journal of Applied Statistics / v.25, no.5, 2012 , pp. 859-864 More about this Journal
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;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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