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Relevant bibliographies by topics / Zero-inflated Poisson model

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Journal articles

Academic literature on the topic 'Zero-inflated Poisson model'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Zero-inflated Poisson model"

1

Lim, Hwa Kyung, Wai Keung Li, and Philip L. H. Yu. "Zero-inflated Poisson regression mixture model." Computational Statistics & Data Analysis 71 (March 2014): 151–58. http://dx.doi.org/10.1016/j.csda.2013.06.021.

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2

Tang, Yi, and Wan Tang. "Testing modified zeros for Poisson regression models." Statistical Methods in Medical Research 28, no. 10-11 (2018): 3123–41. http://dx.doi.org/10.1177/0962280218796253.

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Excessive zeros are common in practice and may cause overdispersion and invalidate inferences when fitting Poisson regression models. Zero-inflated Poisson regression models may be applied if there are inflated zeros; however, it is desirable to test if there are inflated zeros before such zero-inflated Poisson models are applied. Assuming a constant probability of being a structural zero in a zero-inflated Poisson regression model, the existence of the inflated zeros may be tested by testing whether the constant probability is zero. In such situations, the Wald, score, and likelihood ratio te

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3

Cheung, Yin Bun, and K. F. Lam. "Bivariate Poisson–Poisson model of zero-inflated absenteeism data." Statistics in Medicine 25, no. 21 (2006): 3707–17. http://dx.doi.org/10.1002/sim.2485.

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4

Lee, Ji-Ho, Tae-Ryon Choi, and Yoon-Sung Wo. "Bayesian Approaches to Zero Inflated Poisson Model." Korean Journal of Applied Statistics 24, no. 4 (2011): 677–93. http://dx.doi.org/10.5351/kjas.2011.24.4.677.

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5

Kassahun, Wondwosen, Thomas Neyens, Christel Faes, Geert Molenberghs, and Geert Verbeke. "A zero-inflated overdispersed hierarchical Poisson model." Statistical Modelling: An International Journal 14, no. 5 (2014): 439–56. http://dx.doi.org/10.1177/1471082x14524676.

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6

Yang, Jun, and Xin Zhang. "Zero-Inflated Poisson Model with Group Data." Advanced Materials Research 569 (September 2012): 627–31. http://dx.doi.org/10.4028/www.scientific.net/amr.569.627.

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The Zero-inflated Poisson model has been widely used in many fields for count data with excessive zeroes. In fact, group data are often collected for many count data, such as cigarette consumption. In order to solve the problem, Zero-inflated Poisson model with group data is investigated in this paper. Parameter estimation is given by the maximum likelihood estimate, model selection is discussed by the Chi-square test, and one real example is given for application in the end.

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7

Akbarzadeh Baghban, Alireza, Asma Pourhoseingholi, Farid Zayeri, Ali Akbar Jafari, and Seyed Moayed Alavian. "Application of Zero-Inflated Poisson Mixed Models in Prognostic Factors of Hepatitis C." BioMed Research International 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/403151.

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Background and Objectives. In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C.Methods. The data was collected from a longitudinal study during 2005–2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the prop

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8

Tawiah, Kassim, Wahab Abdul Iddrisu, and Killian Asampana Asosega. "Zero-Inflated Time Series Modelling of COVID-19 Deaths in Ghana." Journal of Environmental and Public Health 2021 (April 30, 2021): 1–9. http://dx.doi.org/10.1155/2021/5543977.

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Discrete count time series data with an excessive number of zeros have warranted the development of zero-inflated time series models to incorporate the inflation of zeros and the overdispersion that comes with it. In this paper, we investigated the characteristics of the trend of daily count of COVID-19 deaths in Ghana using zero-inflated models. We envisaged that the trend of COVID-19 deaths per day in Ghana portrays a general increase from the onset of the pandemic in the country to about day 160 after which there is a general decrease onward. We fitted a zero-inflated Poisson autoregressive

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9

He, Hua, Hui Zhang, Peng Ye, and Wan Tang. "A test of inflated zeros for Poisson regression models." Statistical Methods in Medical Research 28, no. 4 (2017): 1157–69. http://dx.doi.org/10.1177/0962280217749991.

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Excessive zeros are common in practice and may cause overdispersion and invalidate inference when fitting Poisson regression models. There is a large body of literature on zero-inflated Poisson models. However, methods for testing whether there are excessive zeros are less well developed. The Vuong test comparing a Poisson and a zero-inflated Poisson model is commonly applied in practice. However, the type I error of the test often deviates seriously from the nominal level, rendering serious doubts on the validity of the test in such applications. In this paper, we develop a new approach for t

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10

Purhadi, Yuliani Setia Dewi, and Luthfatul Amaliana. "Zero Inflated Poisson and Geographically Weighted Zero- Inflated Poisson Regression Model: Application to Elephantiasis (Filariasis) Counts Data." Journal of Mathematics and Statistics 11, no. 2 (2015): 52–60. http://dx.doi.org/10.3844/jmssp.2015.52.60.

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