Comparison of Zero Inflated Poisson (ZIP) Regression, Zero Inflated Negative Binomial Regression (ZINB) and Binomial Negative Hurdle Regression (HNB) to Model Daily Cigarette Consumption Data for Adult Population in Indonesia

Authors

  • Drajat Indra Purnama Badan Pusat Statistik Kabupaten Parigi Moutong, Sulawesi Tengah

DOI:

https://doi.org/10.20956/j.v17i3.12278

Keywords:

ZIP, ZINB, HNB, Cigarette Consumption

Abstract

Smoking is a habit that is not good for health. Smoking habits are generally practiced by adults but it is possible for teenagers to do so.The Report of Southeast Asia Tobacco Control Alliance (SEATCA) entitled The Tobacco Control Atlas, ASEAN Region shows that Indonesia is the country with the highest number of smokers in ASEAN, namely 65.19 million people. This figure is equivalent to 34 percent of the total population of Indonesia in 2016. Based on these data, the authors are interested in modeling the daily cigarette consumption data for adults in Indonesia obtained from the 2015 Indonesia Family Life Survey. The variables used include the variable amount of cigarette consumption, education, level of welfare and income per month. The author wants to compare the best model that can be used to model the daily cigarette consumption of adults in Indonesia. The models being compared are Zero Inflated Poisson Regression (ZIP), Zero Inflated Negative Binomial Regression (ZINB) and Binomial Negative Hurdle Regression (HNB). The comparison results of the three models obtained that the best model is the Zero Inflated Negative Binomial (ZINB) Regression model because it has the smallest Akaike's Information Criterion (AIC) value.

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References

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Published

2021-05-12

How to Cite

Purnama, D. I. (2021). Comparison of Zero Inflated Poisson (ZIP) Regression, Zero Inflated Negative Binomial Regression (ZINB) and Binomial Negative Hurdle Regression (HNB) to Model Daily Cigarette Consumption Data for Adult Population in Indonesia. Jurnal Matematika, Statistika Dan Komputasi, 17(3), 357-369. https://doi.org/10.20956/j.v17i3.12278

Issue

Vol. 17 No. 3 (2021): May, 2021

Section

Research Articles

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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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