Monitoring the alternating renewal processes with Weibull window-censored data

References

• Ahmadi, M. V., & Doostparast, M. (2022). Bayesian analysis of the lifetime performance index on the basis of progressively censored Weibull observations. Quality Technology & Quantitative Management, 19(2), 187–214. https://doi.org/10.1080/16843703.2021.1963032
   Web of Science ®Google Scholar
• Alamer, E. M. S. (2017), CUSUM Control Charts for Censored Gamma Distributed Quality Measurements (Doctoral dissertation).
   Google Scholar
• Alvarez, E. E. (2005). Smoothed nonparametric estimation in window censored semi-Markov processes. Journal of Statistical Planning and Inference, 131(2), 209–229. https://doi.org/10.1016/j.jspi.2004.03.003
   Web of Science ®Google Scholar
• Alvarez, E. E. (2006). Maximum likelihood estimation in alternating renewal processes under window censoring. Stochastic Models, 22(1), 55–76. https://doi.org/10.1080/15326340500481739
   Web of Science ®Google Scholar
• Birmingham, D. J., Nagaraja, H. N., Rovin, B. H., Spetie, L., Zhao, Y., & Li, X., … Hebert, L. A. (2006). Fluctuation in self-perceived stress and increased risk of flare in patients with lupus nephritis carrying the serotonin receptor 1A-C1019 G allele. Journal of the American College of Rheumatology, 54(10), 3291–32996.
   Google Scholar
• Chakraborty, N., & Mahmood, T. (2021). Failure rate monitoring in generalized gamma-distributed process. Quality Technology & Quantitative Management, 18(6), 718–739. https://doi.org/10.1080/16843703.2021.1953241
   Web of Science ®Google Scholar
• Chan, Y., Han, B., & Pascual, F. (2015). Monitoring the Weibull shape parameter with type II censored data. Quality and Reliability Engineering International, 31(5), 741–760. https://doi.org/10.1002/qre.1631
   Web of Science ®Google Scholar
• Chin, H. C., & Quek, S. T. (1997). Measurement of traffic conflicts. Safety Science, 26(3), 169–185. https://doi.org/10.1016/S0925-7535(97)00041-6
   Web of Science ®Google Scholar
• Dickinson, R. M., Roberts, D. A. O., Driscoll, A. R., Woodall, W. H., & Vining, G. G. (2014). CUSUM charts for monitoring the characteristic life of censored Weibull lifetimes. Journal of Quality Technology, 46(4), 340–358. https://doi.org/10.1080/00224065.2014.11917976
   Web of Science ®Google Scholar
• Erto, P., Pallotta, G., Palumbo, B., & Mastrangelo, C. M. (2018). The performance of semi-empirical Bayesian control charts for monitoring Weibull data. Quality Technology & Quantitative Management, 15(1), 69–86. https://doi.org/10.1080/16843703.2017.1304036
   Web of Science ®Google Scholar
• Guo, F., Klauer, S. G., Hankey, J. M., & Dingus, T. A. (2010). Near crashes as crash surrogate for naturalistic driving studies. Transportation Research Record, 2147(1), 66–74. https://doi.org/10.3141/2147-09
   Google Scholar
• Guo, B., & Wang, B. X. (2014). Control charts for monitoring the Weibull shape parameter based on type-II censored sample. Quality and Reliability Engineering International, 30(1), 13–24. https://doi.org/10.1002/qre.1473
   Web of Science ®Google Scholar
• Karlin, S. (2014). A first course in stochastic processes. Academic Press.
   Google Scholar
• Lee, P. H. (2021). Economic design of a CEV x control chart for determining optimal right-censored times. Quality Technology & Quantitative Management, 18(4), 418–431. https://doi.org/10.1080/16843703.2021.1876971
   Web of Science ®Google Scholar
• Lucas, J. M., & Saccucci, M. S. (1990). Exponentially weighted moving average control schemes: Properties and enhancements. Technometrics, 32(1), 1–12. https://doi.org/10.1080/00401706.1990.10484583
   Web of Science ®Google Scholar
• Nelson, W. B. (2003). Recurrent events data analysis for product repairs, disease recurrences, and other applications. Society for Industrial and Applied Mathematics.
   Google Scholar
• Pascual, F., & Li, S. (2012). Monitoring the Weibull shape parameter by control charts for the sample range of type II censored data. Quality and Reliability Engineering International, 28(2), 233–246. https://doi.org/10.1002/qre.1239
   Web of Science ®Google Scholar
• Pascual, F., & Zhang, H. (2011). Monitoring the Weibull shape parameter by control charts for the sample range. Quality and Reliability Engineering International, 27(1), 15–25. https://doi.org/10.1002/qre.1099
   Web of Science ®Google Scholar
• Perkins, S. R., & Harris, J. L. (1968). Traffic conflict characteristics-accident potential at intersections. Highway Research Record, 225, 35–43 .
   Google Scholar
• Qiu, P. (2013). Introduction to statistical process control. CRC press.
   Google Scholar
• Rootzén, H., & Zholud, D. (2016). Tail estimation for window-censored processes. Technometrics, 58(1), 95–103. https://doi.org/10.1080/00401706.2014.995834
   Web of Science ®Google Scholar
• Steiner, S. H., & Mackay, R. J. (2000). Monitoring processes with highly censored data. Journal of Quality Technology, 32(3), 199–208. https://doi.org/10.1080/00224065.2000.11979996
   Web of Science ®Google Scholar
• Steiner, S. H., & Mackay, R. J. (2001). Monitoring processes with data censored owing to competing risks by using exponentially weighted moving average control charts. Journal of the Royal Statistical Society: Series C (Applied Statistics), 50(3), 293–302.
   Google Scholar
• Vardi, Y. (1982). Nonparametric estimation in the presence of length bias. Annals of Statistics, 10(2), 616–620.
   Web of Science ®Google Scholar
• Wang, Y., Guo, L., Wen, M., & Kang, R. (2021). Belief availability for repairable systems based on uncertain alternating renewal process. IEEE Transactions on Reliability, 70(3), 1242–1254. https://doi.org/10.1109/TR.2020.3047599
   Web of Science ®Google Scholar
• Xiao, S., Kottas, A., Sansó, B., & Kim, H. (2021). Nonparametric Bayesian modeling and estimation for renewal processes. Technometrics, 63(1), 100–115. https://doi.org/10.1080/00401706.2019.1693428
   Web of Science ®Google Scholar
• Yao, K., & Gao, J. (2014). Uncertain random alternating renewal process with application to interval availability. IEEE Transactions on Fuzzy Systems, 23(5), 1333–1342. https://doi.org/10.1109/TFUZZ.2014.2360551
   Web of Science ®Google Scholar
• Zhang, L., & Chen, G. (2004). EWMA charts for monitoring the mean of censored Weibull lifetimes. Journal of Quality Technology, 36(3), 321–328. https://doi.org/10.1080/00224065.2004.11980277
   Web of Science ®Google Scholar
• Zhao, Y., & Nagaraja, H. N. (2011). Fisher information in window censored renewal process data and its applications. Annals of the Institute of Statistical Mathematics, 63(4), 791–825. https://doi.org/10.1007/s10463-009-0252-2
   Web of Science ®Google Scholar
• Zhu, Y., Yashchin, E., & Hosking, J. R. M. (2014). Parametric estimation for window censored recurrence data. Technometrics, 56(1), 55–66. https://doi.org/10.1080/00401706.2013.804442
   Web of Science ®Google Scholar