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Zero Inflation Model for Food Poisoning index

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Authors
김병집
Advisor
조신섭
Major
통계학과
Issue Date
2012-02
Publisher
서울대학교 대학원
Description
학위논문 (석사)-- 서울대학교 대학원 : 통계학과, 2012. 2. 조신섭.
Abstract
In this thesis, we review the event count data analysis methods. In particular, we focus on the zero-inflated regression and time series models in contrast to the well-known GLM regression model. The event count regression models including Poisson regression and negative binomial regression are introduced. Then, we analyze the food poisoning data using the zero-inflated models which consider mixed probability distributions. It is well known that the zero-inflated models can catch the special characteristics such as the over-dispersion and zero-inflation of the real life data. We compare the performances of the zero-inflated models with the other models using Vuong statistic and propose new food-poisoning index based on the zero-inflated model.
Language
eng
URI
http://hdl.handle.net/10371/155780

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College of Natural Sciences (자연과학대학)Dept. of Statistics (통계학과)Theses (Master's Degree_통계학과)
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