Model Regresi Hurdle Negative Binomial (HNB) untuk Pemodelan Konsumsi Rokok di Provinsi Sulawesi Tengah

D. I. Purnama
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Abstract

The average expenditure on cigarettes per capita in Sulawesi Tengah Province has increased in 2020. There are several factors that can affect a person's cigarette consumption including gender, age, education and health. To model cigarette consumption with several influencing factors can be use the poison regression model or the Zero Inflated Poisson (ZIP) model. However, the two regression models cannot solve the excess zero and overdispersion problems so use the Hurdle Negative Binomial (HNB) regression model. The results of the analysis of cigarette consumption data in Central Sulawesi Province using the HNB model provide the best modeling results compared to the poisson regression model and the ZIP model because it has the smallest Akaike's Information Criterion (AIC) value. The results of testing the factors that significantly influence cigarette consumption in Central Sulawesi Province in the HNB regression model, namely the count model are gender, age and health. Whereas in the zerohurdle model, it is gender, age and education.
用于苏拉威西省香烟消费建模的负边护轴模型
2020年,苏拉威西登加省的人均卷烟支出有所增加。有几个因素会影响一个人的香烟消费,包括性别、年龄、教育和健康状况。对卷烟消费的影响因素进行建模,可以采用毒物回归模型或零膨胀泊松(ZIP)模型。然而,这两种回归模型都不能解决过零和过分散问题,因此采用了障碍负二项(HNB)回归模型。使用HNB模型对中苏拉威西省卷烟消费数据进行分析的结果,由于其赤客信息准则(Akaike’s Information Criterion, AIC)值最小,与泊松回归模型和ZIP模型相比,建模效果最好。在HNB回归模型即计数模型中,检验对中苏拉威西省卷烟消费有显著影响的因素为性别、年龄和健康状况。而在零障碍模型中,则是性别、年龄和教育程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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