Application of zero-and-one-inflated negative binomial regression model in COVID−19 epidemic analysis

MA Qiaoling; XIAO Xiang

doi:10.12299/jsues.21-0235

Volume 36 Issue 2

Jun. 2022

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Article Navigation > Journal of Shanghai University of Engineering Science > 2022 > 36(2): 212-217

MA Qiaoling, XIAO Xiang. Application of zero-and-one-inflated negative binomial regression model in COVID−19 epidemic analysis[J]. Journal of Shanghai University of Engineering Science, 2022, 36(2): 212-217. doi: 10.12299/jsues.21-0235

Citation:

MA Qiaoling, XIAO Xiang. Application of zero-and-one-inflated negative binomial regression model in COVID−19 epidemic analysis[J]. Journal of Shanghai University of Engineering Science, 2022, 36(2): 212-217. doi: 10.12299/jsues.21-0235

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Application of zero-and-one-inflated negative binomial regression model in COVID−19 epidemic analysis

doi: 10.12299/jsues.21-0235

MA Qiaoling,
XIAO Xiang^,

School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai 201620, China

Received Date: 2021-10-29
Available Online: 2022-11-16
Publish Date: 2022-06-30

Abstract

Abstract

Count datas with excess zeros and ones arise frequently in the field of public health. In order to fit the kind of data, a zero-and-one-inflated negative binomial (ZOINB) distribution and its regression model were adopted for analysis. Based on data augmentation strategy and Pólya−Gamma latent variables Bayesian inference was used to estimate the parameters of ZOINB regression model. Finally, one corona virus disease 2019 (COVID−19) death data-set from Hubei Province in China was analyzed. The result illustrates that ZOINB regression model can achieve better fitting effect.

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References(13)

References

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