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Zero-inflated Poisson regression mixture model

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  • Lim, Hwa Kyung
  • Li, Wai Keung
  • Yu, Philip L.H.

Abstract

Excess zeros and overdispersion are common phenomena that limit the use of traditional Poisson regression models for modeling count data. Both excess zeros and overdispersion caused by unobserved heterogeneity are accounted for by the proposed zero-inflated Poisson (ZIP) regression mixture model. To estimate the parameters of the model, an EM algorithm with an embedded iteratively reweighted least squares method is implemented. The parameter estimation performance of the proposed model is evaluated through simulation studies. The ZIP regression mixture model is applied to the DMFT index dataset, which contains excess zeros and overdispersion. Comparisons of several other models commonly used for such data with the ZIP regression mixture model show that, in general, the latter model fits the data well.

Suggested Citation

  • Lim, Hwa Kyung & Li, Wai Keung & Yu, Philip L.H., 2014. "Zero-inflated Poisson regression mixture model," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 151-158.
    • Handle: RePEc:eee:csdana:v:71:y:2014:i:c:p:151-158
    DOI: 10.1016/j.csda.2013.06.021
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    References listed on IDEAS

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    Cited by:

    1. Marco Gemma & Fulvia Pennoni & Roberta Tritto & Massimo Agostoni, 2021. "Risk of adverse events in gastrointestinal endoscopy: Zero-inflated Poisson regression mixture model for count data and multinomial logit model for the type of event," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-16, June.
    2. Wenchen Liu & Yincai Tang & Ancha Xu, 2021. "Zero-and-one-inflated Poisson regression model," Statistical Papers, Springer, vol. 62(2), pages 915-934, April.
    3. Fatemeh Hassanzadeh & Iraj Kazemi, 2017. "Regression modeling of one-inflated positive count data," Statistical Papers, Springer, vol. 58(3), pages 791-809, September.
    4. Minji Kim & Hee-Seok Oh & Yaeji Lim, 2023. "Zero-Inflated Time Series Clustering Via Ensemble Thick-Pen Transform," Journal of Classification, Springer;The Classification Society, vol. 40(2), pages 407-431, July.
    5. Jussiane Nader Gonçalves & Wagner Barreto-Souza, 2020. "Flexible regression models for counts with high-inflation of zeros," METRON, Springer;Sapienza Università di Roma, vol. 78(1), pages 71-95, April.
    6. Počuča, Nikola & Jevtić, Petar & McNicholas, Paul D. & Miljkovic, Tatjana, 2020. "Modeling frequency and severity of claims with the zero-inflated generalized cluster-weighted models," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 79-93.

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