References
- Alevizakos, V., and C. Koukouvinos. 2020. A generally weighted moving average control chart for zero‐inflated Poisson processes. Quality and Reliability Engineering International 36 (2):675–704. doi:10.1002/qre.2599.
- Alevizakos, V., and C. Koukouvinos. 2021. Monitoring of zero-inflated binomial processes with a DEWMA control chart. Journal of Applied Statistics 48 (7):1319–38. doi:10.1080/02664763.2020.1761950.
- Aly, A. A., N. A. Saleh, and M. A. Mahmoud. 2022. An adaptive EWMA control chart for monitoring zero-inflated Poisson processes. Communications in Statistics-Simulation and Computation 51 (4):1564–77.
- Böhning, D. 1998. Zero‐inflated Poisson models and CA MAN: A tutorial collection of evidence. Biometrical Journal 40 (7):833–43. doi:10.1002/(SICI)1521-4036(199811)40:7<833::AID-BIMJ833>3.0.CO;2-O.
- Bourke, P. D. 1991. Detecting a shift in fraction nonconforming using run-length control charts with 100% inspection. Journal of Quality Technology 23 (3):225–38. doi:10.1080/00224065.1991.11979328.
- Crosier, R. B. 1986. A new two-sided cumulative sum quality control scheme. Technometrics 28 (3):187–94. doi:10.1080/00401706.1986.10488126.
- Davis, R. B., and W. H. Woodall. 2002. Evaluating and improving the synthetic control chart. Journal of Quality Technology 34 (2):200–8. doi:10.1080/00224065.2002.11980146.
- He, S., W. Huang, and W. H. Woodall. 2012. CUSUM charts for monitoring a zero-inflated Poisson process. Quality and Reliability Engineering International 28 (2):181–92. doi:10.1002/qre.1228.
- He, S., S. Li, and Z. He. 2014. A combination of CUSUM charts for monitoring a zero-inflated Poisson process. Communications in Statistics - Simulation and Computation 43 (10):2482–97. doi:10.1080/03610918.2012.753082.
- Hu, Q., and L. Liu. 2021. Weighted score test based EWMA control charts for Zero-Inflated Poisson Models. Computers & Industrial Engineering 152:106966. doi:10.1016/j.cie.2020.106966.
- Johnson, N. L. A. W. Kemp, and S. Kotz. 2005. Univariate discrete distributions. 3rd ed. Hoboken, NJ: John Wiley & Sons, Inc.
- Knoth, S. 2016. The case against the use of synthetic control charts. Journal of Quality Technology 48 (2):178–95. doi:10.1080/00224065.2016.11918158.
- Knoth, S. 2021. Steady-state average run length(s): Methodology, formulas, and numerics. Sequential Analysis 40 (3):405–26. doi:10.1080/07474946.2021.1940501.
- Lambert, D. 1992. Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics 34 (1):1–14. doi:10.2307/1269547.
- Machado, M. A. G., and A. F. B. Costa. 2014. A side-sensitive synthetic chart combined with an X chart. International Journal of Production Research 52 (11):3404–16. doi:10.1080/00207543.2013.879221.
- Mahmood, T., and M. Xie. 2019. Models and monitoring of zero‐inflated processes: The past and current trends. Quality and Reliability Engineering International 35 (8):2540–57. doi:10.1002/qre.2547.
- Montgomery, D. C. 2012. Introduction to statistical quality control. 7th ed. New York: John Wiley & Sonds, Inc.
- Mukherjee, A., and R. Sen. 2018. Optimal design of Shewhart-Lepage type schemes and its application in monitoring service quality. European Journal of Operational Research 266 (1):147–67. doi:10.1016/j.ejor.2017.09.013.
- Murat, M., and D. Szynal. 1998. Non–zero inflated modified power series distributions. Communications in Statistics - Theory and Methods 27 (12):3047–64. doi:10.1080/03610929808832272.
- R Core Team. 2022. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.r-project.org/.
- Rakitzis, A. C., P. Castagliola, and P. E. Maravelakis. 2016a. A two-parameter general inflated Poisson distribution: Properties and applications. Statistical Methodology 29:32–50. doi:10.1016/j.stamet.2015.10.002.
- Rakitzis, A. C., P. Castagliola, and P. E. Maravelakis. 2016b. On the modelling and monitoring of general inflated Poisson processes. Quality and Reliability Engineering International 32 (5):1837–51. doi:10.1002/qre.1917.
- Rakitzis, A. C., P. Castagliola, and P. E. Maravelakis. 2018. Cumulative sum control charts for monitoring geometrically inflated Poisson processes: An application to infectious disease counts data. Statistical Methods in Medical Research 27 (2):622–41. doi:10.1177/0962280216641985.
- Rakitzis, A. C., S. Chakraborti, S. C. Shongwe, M. A. Graham, and M. B. C. Khoo. 2019. An overview of synthetic‐type control charts: Techniques and methodology. Quality and Reliability Engineering International 35 (7):2081–96. doi:10.1002/qre.2491.
- Ridout, M., J. Hinde, and C. G. Demétrio. 2001. A score test for testing a zero-inflated Poisson regression model against zero-inflated negative binomial alternatives. Biometrics 57 (1):219–23. doi:10.1111/j.0006-341x.2001.00219.x.
- Scariano, S. M., and M. E. Calzada. 2009. The generalized synthetic chart. Sequential Analysis 28 (1):54–68. doi:10.1080/07474940802619261.
- Tang, Y., W. Liu, and A. Xu. 2017. Statistical inference for zero-and-one inflated Poisson models. Statistical Theory and Related Fields 1 (2):216–26. doi:10.1080/24754269.2017.1400419.
- Tsai, M. H., and T. H. Lin. 2017. Modeling data with a truncated and inflated Poisson distribution. Statistical Methods & Applications 26 (3):383–401. doi:10.1007/s10260-017-0377-z.
- Wagh, Y. S., and K. K. Kamalja. 2018. Zero-inflated models and estimation in zero-inflated Poisson distribution. Communications in Statistics - Simulation and Computation 47 (8):2248–65. doi:10.1080/03610918.2017.1341526.
- Wang, Z., and P. Qiu. 2018. Count data monitoring: Parametric or nonparametric? Quality and Reliability Engineering International 34 (8):1763–74. doi:10.1002/qre.2368.
- Wu, Z., Y. Ou, P. Castagliola, and M. B. C. Khoo. 2010. A combined synthetic &Xchart for monitoring the process mean. International Journal of Production Research 48 (24):7423–36.
- Wu, Z., and T. A. Spedding. 2000. A synthetic control chart for detecting small shifts in the process mean. Journal of Quality Technology 32 (1):32–8. doi:10.1080/00224065.2000.11979969.
- Xu, H. Y., M. Xie, and T. N. Goh. 2014. Objective Bayes analysis of zero-inflated Poisson distribution with application to healthcare data. IIE Transactions 46 (8):843–52. doi:10.1080/0740817X.2013.770190.