The multivariate component zero-inflated Poisson model for correlated count data analysis

Wu，Qin1; Tian，Guo Liang2; Li，Tao2; Tang，Man Lai3; Zhang，Chi4

2023

10.1111/anzs.12395

Australian and New Zealand Journal of Statistics   影响因子和分区

1369-1473

1467-842X

Multivariate zero-inflated Poisson (ZIP) distributions are important tools for modelling and analysing correlated count data with extra zeros. Unfortunately, existing multivariate ZIP distributions consider only the overall zero-inflation while the component zero-inflation is not well addressed. This paper proposes a flexible multivariate ZIP distribution, called the multivariate component ZIP distribution, in which both the overall and component zero-inflations are taken into account. Likelihood-based inference procedures including the calculation of maximum likelihood estimates of parameters in the model without and with covariates are provided. Simulation studies indicate that the performance of the proposed methods on the multivariate component ZIP model is satisfactory. The Australia health care utilisation data set is analysed to demonstrate that the new distribution is more appropriate than the existing multivariate ZIP distributions.

component zero-inflation multivariate zero-inflated Poisson overall zero-inflation stochastic representation univariate zero-inflated Poisson

SCI

英语

其他

National Natural Science Foundation of China["12171167","12171076","12171225","11871124","UGC/FDS14/P05/20","20200810141501001"] ; University Stability Support Plan of Shenzhen City[11771199] ; Research Grants Council of Hong Kong Special Administrative Region["11801380","20200925153807002"] ; Shenzhen Science and Technology Program[700006]

Mathematics

Statistics & Probability

WOS:001076996300004

WILEY

MATHEMATICS

2-s2.0-85169142630

Scopus

1.Department of Statistics,School of Mathematical Sciences,South China Normal University,Guangzhou,Guangdong,510631,China
2.Department of Statistics and Data Science,Southern University of Science and Technology,Shenzhen,Guangdong,518055,China
3.Department of Physics,Astronomy and Mathematics,School of Physics,Engineering & Computer Science,University of Hertfordshire,Hertfordshire,United Kingdom
4.College of Economics,Shenzhen University,Shenzhen,Guangdong,518055,China

Wu，Qin,Tian，Guo Liang,Li，Tao,et al. The multivariate component zero-inflated Poisson model for correlated count data analysis[J]. Australian and New Zealand Journal of Statistics,2023,65(3).

Wu，Qin,Tian，Guo Liang,Li，Tao,Tang，Man Lai,&Zhang，Chi.(2023).The multivariate component zero-inflated Poisson model for correlated count data analysis.Australian and New Zealand Journal of Statistics,65(3).

Wu，Qin,et al."The multivariate component zero-inflated Poisson model for correlated count data analysis".Australian and New Zealand Journal of Statistics 65.3(2023).