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A Zero-Inated Model for Insurance Data
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 Title & Authors
A Zero-Inated Model for Insurance Data
Choi, Jong-Hoo; Ko, In-Mi; Cheon, Soo-Young;
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 Abstract
When the observations can take only the non-negative integer values, it is called the count data such as the numbers of car accidents, earthquakes, or insurance coverage. In general, the Poisson regression model has been used to model these count data; however, this model has a weakness in that it is restricted by the equality of the mean and the variance. On the other hand, the count data often tend to be too dispersed to allow the use of the Poisson model in practice because the variance of data is significantly larger than its mean due to heterogeneity within groups. When overdispersion is not taken into account, it is expected that the resulting parameter estimates or standard errors will be inefficient. Since coverage is the main issue for insurance, some accidents may not be covered by insurance, and the number covered by insurance may be zero. This paper considers the zero-inflated model for the count data including many zeros. The performance of this model has been investigated by using of real data with overdispersion and many zeros. The results indicate that the Zero-Inflated Negative Binomial Regression Model performs the best for model evaluation.
 Keywords
Count data;overdispersion;zero-inflated model;insurance coverage;
 Language
Korean
 Cited by
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교통사고건수에 대한 포아송 회귀와 음이항 회귀모형 적합,정재풍;최종후;

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중소기업 청년인턴 이직횟수 결정요인 분석,박성익;류장수;김종한;조장식;

Journal of the Korean Data and Information Science Society, 2015. vol.26. 2, pp.387-397 crossref(new window)
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재학 중 경험한 일자리 수와 구직기간 결정요인 분석,조장식;

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The study on the determinants of the number of job changes, Journal of the Korean Data and Information Science Society, 2015, 26, 2, 387  crossref(new windwow)
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