[
Akinpelu K.P., Yusuf O.B., Akpa O.M., Gbolahan A.O. (2016): Zero Inflated Regression Models with Application to Malaria Surveillance Data. International Journal of Statistics and Application 6(4): 223-234.
]Search in Google Scholar
[
Cao Y., Zhang A., Li H. (2017): Microbial composition estimation from sparse count data. ArXiv. Available at:arXiv:1706.02380.
]Search in Google Scholar
[
David I., Adubisi O., Farouk B., Adehi M. (2020): Assessing MSMEs Growth Through ROSCA Involvement Using Paired t-Test and One Sample Proportion Test. Journal of Social and Economic Statistics, 9(2): 30-42, https://doi.org/10.2478/jses-2020-0011
]Search in Google Scholar
[
Li H. (2015): Microbiome, metagenomics, and high-dimensional compositional data analysis. Annual Review of Statistics and Its Application 2: 73–94.
]Search in Google Scholar
[
Sohn M.B., Li H. (2018): A GLM-based latent variable ordination method for microbiome samples. Biometrics, 74: 448–457. [PubMed: 28991375]
]Search in Google Scholar
[
Xu T., Demmer R.T., Li G. (2021): Zero-inflated Poisson factor model with application to microbiome read counts. Biometrics, 77(1): 91-101, https://doi.org/10.1111/biom.13272
]Search in Google Scholar
[
Altun E. (2018): A new zero-inflated regression model with application. Journal of Statisticians: Statistics and Actuarial Sciences, 11(2): 73-80.
]Search in Google Scholar
[
Workie M.S., Azene A.G. (2021): Bayesian zero-inflated regression model with application to under-five child mortality. Journal of Big Data 8(4), https://doi.org/10.1186/s40537-020-00389-4
]Search in Google Scholar
[
Lambert D. (1992): Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1): 1–14.
]Search in Google Scholar
[
Ridout M., Demétrio C.G., Hinde J. (1998): Models for count data with many zeros. Proceedings of the XIXth International Biometric Conference 19(1): 179–192.
]Search in Google Scholar
[
Sharp E., Parson S., Jefferson B. (2006): Coagulation of NOM: linking character to treatment. Water Science and Technology, 53(7): 67-76.
]Search in Google Scholar
[
Zafakali N.S., Wan M.A., Ahmad W. (2013): Modelling and Handling Overdispersion Health Science data with Zero-inflated Poisson Model. Journal of Modern Applied Statistical Methods, 12(1): 255-260.
]Search in Google Scholar
