Zero-Inflated Negative Binomial model to Overcome Excess Zeros Count in Motorcycles Road Accident

被引：0
|
作者：
Sapuan, M. S. [1 ]
Razali, A. M. [1 ,2 ]
Zamzuri, Z. H. [1 ,2 ]
机构：
[1] Univ Kebangsaan Malaysia, Fac Sci & Technol, Sch Math Sci, Ukm Bangi 43600, Malaysia
[2] Univ Kebangsaan Malaysia, Ctr Modeling & Data Anal DELTA, Ukm Bangi 43600, Malaysia
来源：
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS | 2016年 / 55卷 / 02期
关键词：
Poisson model; negative binomial model; hurdle model; zero-inflated model; and motorcycle accident;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Motorcycle is becoming one of the most important transportation modes and its intensity usage is increasing tremendously on the roadway. Therefore, problems of its reliability and safety are highly well-defined and discussed. In this paper, the most used model of count data for accident modeling namely Poisson and negative binomial regression are presented along with the zero-augmented model namely zero-inflated Poisson, hurdle Poisson, zero-inflated negative binomial and hurdle negative binomial will be fitted to a real motorcycle road accident data. The model validation result shows that zero-inflated negative binomial fit the data well and the highest traffic offenses and locations factors are determined.
引用
收藏
页码：46 / 56
页数：11
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