References
- Arif, F., Noor-Ul-Amin, M., & Hanif, M. (2021). Joint monitoring of mean and variance using likelihood ratio test statistic with measurement error. Quality Technology & Quantitative Management, 18(2), 202–224. https://doi.org/https://doi.org/10.1080/16843703.2020.1819138
- Aslam, M., Azam, M., & Jun, C. H. (2015). A new control chart for exponential distributed life using EWMA. Transactions of the Institute of Measurement and Control, 37(2), 205–210. https://doi.org/https://doi.org/10.1177/0142331214537293
- Capizzi, G., & Masarotto, G. (2013). Phase I distribution-free analysis of univariate data. Journal of Quality Technology, 45(3), 273–284. https://doi.org/https://doi.org/10.1080/00224065.2013.11917938
- Cascos, I. (2021). Simultaneous monitoring of origin and scale in left-bounded processes via depth. AStA Adv Stat Anal. https://doi.org/https://doi.org/10.1007/s10182-021-00401-z
- Chen, G., & Cheng, S. W. (1998). Max chart: Combining X-bar chart and S chart. Statistica Sinica, 8(1), 263–271. https://www.jstor.org/stable/24306354
- Cheng, S. W., & Thaga, K. (2006). Single variables control charts: An overview. Quality and Reliability Engineering International, 22(7), 811–820. https://doi.org/https://doi.org/10.1002/qre.730
- Chong, Z. L., Mukherjee, A., & Marozzi, M. (2021). Simultaneous monitoring of origin and scale of a shifted exponential process with unknown and estimated parameters. Quality and Reliability Engineering International, 37(1), 242–261. https://doi.org/https://doi.org/10.1002/qre.2732
- Erfanian, M., Sadeghpour Gildeh, B., & Reza Azarpazhooh, M. (2021). A new approach for monitoring healthcare performance using generalized additive profiles. Journal of Statistical Computation and Simulation, 91(1), 167–179. https://doi.org/https://doi.org/10.1080/00949655.2020.1807981
- Faraz, A., Woodall, W. H., & Heuchenne, C. (2015). Guaranteed conditional performance of the control chart with estimated parameters. International Journal of Production Research, 53(14), 4405–4413. https://doi.org/https://doi.org/10.1080/00207543.2015.1008112
- Gan, F. F. (1991). An optimal design of CUSUM quality control charts. Journal of Quality Technology, 23(4), 279–286. https://doi.org/https://doi.org/10.1080/00224065.1991.11979343
- Gan, F. F. (1995). Joint monitoring of process mean and variance using exponentially weighted moving average control charts. Technometrics, 37(4), 446–453. https://doi.org/https://doi.org/10.1080/00401706.1995.10484377
- Hou, S., & Yu, K. (2021). A nonparametric CUSUM control chart for process distribution change detection and change type diagnosis. International Journal of Production Research, 59(4), 1166–1186. https://doi.org/https://doi.org/10.1080/00207543.2020.1721588
- Hu, X. L., Castagliola, P., & Tang, A. A. (2019). Conditional design of the CUSUM median chart for the process position when process parameters are unknown. Journal of Statistical Computation and Simulation, 89(13), 2468–2488. https://doi.org/https://doi.org/10.1080/00949655.2019.1622703
- Huang, S., Mukherjee, A., & Yang, J. (2018). Two CUSUM schemes for simultaneous monitoring of parameters of a shifted exponential time to events. Quality and Reliability Engineering International, 34(6), 1158–1173. https://doi.org/https://doi.org/10.1002/qre.2314
- Kao, S. C. (2010). Normalization of the origin-shifted exponential distribution for control chart construction. Journal of Applied Statistics, 37(7), 1067–1087. https://doi.org/https://doi.org/10.1080/02664760802571333
- Keshavarz, M., Asadzadeh, S., & Niaki, S. T. A. (2021). Risk-adjusted frailty-based CUSUM control chart for phase I monitoring of patients’ lifetime. Journal of Statistical Computation and Simulation, 91(2), 334–352. https://doi.org/https://doi.org/10.1080/00949655.2020.1814775
- Khan, N., Aslam, M., & Jun, C. H. (2016). A EWMA control chart for exponential distributed quality based on moving average statistics. Quality and Reliability Engineering International, 32(3), 1179–1190. https://doi.org/https://doi.org/10.1002/qre.1825
- Khoo, M. B. C., Saha, S., Lee, H. C., & Castagliola, P. (2019). Variable sampling interval exponentially weighted moving average median chart with estimated process parameters. Quality and Reliability Engineering International, 35(8), 2732–2748. https://doi.org/https://doi.org/10.1002/qre.2554
- Khusna, H., Mashuri, M., Ahsan, M., Suhartono, S., & Prastyo, D. D. (2020). Bootstrap-based maximum multivariate CUSUM control chart. Quality Technology & Quantitative Management, 17(1), 52–74. https://doi.org/https://doi.org/10.1080/16843703.2018.1535765
- Kim, S. H., Alexopoulos, C., Tsui, K. L., & Wilson, J. R. (2007). A distribution-free tabular CUSUM chart for autocorrelated data. IIE Transactions, 39(3), 317–330. https://doi.org/https://doi.org/10.1080/07408170600743946
- Krishnamoorthy, K., & Xia, Y. (2018). Confidence intervals for a two-parameter exponential distribution: One-and two-sample problems. Communications in Statistics - Theory and Methods, 47(4), 935–952. https://doi.org/https://doi.org/10.1080/03610926.2017.1313983
- Li, C., Mukherjee, A., & Su, Q. (2019b). A distribution-free phase I monitoring scheme for subgroup location and scale based on the multi-sample Lepage statistic. Computers & Industrial Engineering, 129, 259–273. https://doi.org/https://doi.org/10.1016/j.cie.2019.01.013
- Li, C., Mukherjee, A., Su, Q., & Xie, M. (2016). Design and implementation of two CUSUM schemes for simultaneously monitoring the process mean and variance with unknown parameters. Quality and Reliability Engineering International, 32(8), 2961–2975. https://doi.org/https://doi.org/10.1002/qre.1980
- Li, J., Jeske, D. R., Zhou, Y., & Zhang, X. (2019a). A wavelet‐based nonparametric CUSUM control chart for autocorrelated processes with applications to network surveillance. Quality and Reliability Engineering International, 35(2), 644–658. https://doi.org/https://doi.org/10.1002/qre.2427
- Li, Q., Mukherjee, A., song, Z., & Zhang, J. (2021). Phase-II monitoring of exponentially distributed process based on Type-II censored data for a possible shift in location-scale. Journal of Computational and Applied Mathematics, 389, 113315. https://doi.org/https://doi.org/10.1016/j.cam.2020.113315
- Li, Z., Zhang, J., & Wang, Z. (2010). Self-starting control chart for simultaneously monitoring process mean and variance. International Journal of Production Research, 48(15), 4537–4553. https://doi.org/https://doi.org/10.1080/00207540903051692
- Maravelakis, P. E. (2012). Measurement error effect on the CUSUM control chart. Journal of Applied Statistics, 39(2), 323–336. https://doi.org/https://doi.org/10.1080/02664763.2011.590188
- McCracken, A. K., Chakraborti, S., & Mukherjee, A. (2013). Control charts for simultaneous monitoring of unknown mean and variance of normally distributed processes. Journal of Quality Technology, 45(4), 360–376. https://doi.org/https://doi.org/10.1080/00224065.2013.11917944
- Mihalovits, M., & Kemény, S. (2020). Regression control chart with unknown parameters for detection of out-of-trend results in pharmaceutical on-going stability studies. Journal of Pharmaceutical and Biomedical Analysis, 188, 113375. https://doi.org/https://doi.org/10.1016/j.jpba.2020.113375
- Moro, S., Cortez, P., & Rita, P. (2014). A data-driven approach to predict the success of bank telemarketing. Decision Support Systems, 62, 22–31. https://doi.org/https://doi.org/10.1016/j.dss.2014.03.001
- Mukherjee, A., & Chakraborti, S. (2012). A distribution‐free control chart for the joint monitoring of location and scale. Quality and Reliability Engineering International, 28(3), 335–352. https://doi.org/https://doi.org/10.1002/qre.1249
- Mukherjee, A., Cheng, Y., & Gong, M. (2018). A new nonparametric scheme for simultaneous monitoring of bivariate processes and its application in monitoring service quality. Quality Technology & Quantitative Management, 15(1), 143–156. https://doi.org/https://doi.org/10.1080/16843703.2017.1312808
- Mukherjee, A., Chong, Z. L., & Marozzi, M. (2019). Exact simultaneous location-scale tests for two shifted exponential samples. Kybernetika, 55(6), 943–960. https://doi.org/https://doi.org/10.14736/kyb-2019-6-0943
- Mukherjee, A., Li, Q., & Song, Z. (2021). An assessment of the effect of using different mappings and Minkowski distances in joint monitoring of the time-between-event processes. Journal of Computational and Applied Mathematics, 113776. https://doi.org/https://doi.org/10.1016/j.cam.2021.113776
- Mukherjee, A., & Marozzi, M. (2017). A distribution-free phase-II CUSUM procedure for monitoring service quality. Total Quality Management & Business Excellence, 28(11–12), 1227–1263. https://doi.org/https://doi.org/10.1080/14783363.2015.1134266
- Mukherjee, A., McCracken, A. K., & Chakraborti, S. (2015). Control charts for simultaneous monitoring of parameters of a shifted exponential distribution. Journal of Quality Technology, 47(2), 176–192. https://doi.org/https://doi.org/10.1080/00224065.2015.11918123
- Mukherjee, A., & Sen, R. (2018). Optimal design of Shewhart–Lepage type schemes and its application in monitoring service quality. European Journal of Operational Research, 266(1), 147–167. https://doi.org/https://doi.org/10.1016/j.ejor.2017.09.013
- Page, E. S. (1954). Continuous inspection schemes. Biometrika, 41(1), 100–115. https://doi.org/https://doi.org/10.1093/biomet/41.1-2.100
- Raza, M. A., Nawaz, T., & Aslam, M. (2020). On designing CUSUM charts using ratio-type estimators for monitoring the location of normal processes. Scientia Iranica, 27(3), 1593–1605. https://doi.org/https://doi.org/10.24200/SCI.2018.50429.1688
- Roy, A., & Mathew, T. (2005). A generalized confidence limit for the reliability function of a two-parameter exponential distribution. Journal of Statistical Planning and Inference, 128(2), 509–517. https://doi.org/https://doi.org/10.1016/j.jspi.2003.11.012
- Saha, S., Khoo, M. B. C., Ng, P. S., & Chong, Z. L. (2019). Variable sampling interval run sum median charts with known and estimated process parameters. Computers & Industrial Engineering, 127, 571–587. https://doi.org/https://doi.org/10.1016/j.cie.2018.10.049
- Saha, S., Khoo, M. B. C., Teoh., W. L., & Lee, M. H. (2017). Run sum control chart with estimated process parameters. Quality and Reliability Engineering International, 33(8), 1885–1899. https://doi.org/https://doi.org/10.1002/qre.2153
- Saleh, N. A., Mahmoud, M. A., Jones-Farmer, L. A., Zwetsloot, I. N. E. Z., & Woodall, W. H. (2015). Another look at the EWMA control chart with estimated parameters. Journal of Quality Technology, 47(4), 363–382. https://doi.org/https://doi.org/10.1080/00224065.2015.11918140
- Sangnawakij, P., & Niwitpong, S. A. (2017). Confidence intervals for coefficients of variation in two-parameter exponential distributions. Communications in Statistics - Simulation and Computation, 46(8), 6618–6630. https://doi.org/https://doi.org/10.1080/03610918.2016.1208236
- Santiago, E., & Smith, J. (2013). Control charts based on the exponential distribution: Adapting runs rules for the t chart. Quality Engineering, 25(2), 85–96. https://doi.org/https://doi.org/10.1080/08982112.2012.740646
- Song, Z., Mukherjee, A., Ma, N., & Zhang, J. (2021). A class of new nonparametric circular‐grid charts for signal classification. Quality and Reliability Engineering International, 37(6), 2738–2759. https://doi.org/https://doi.org/10.1002/qre.2888
- White, E. M., & Schroeder, R. (1987). A simultaneous control chart. Journal of Quality Technology, 19(1), 1–10. https://doi.org/https://doi.org/10.1080/00224065.1987.11979028
- Xie, M., Goh, T. N., & Ranjan, P. (2002). Some effective control chart procedures for reliability monitoring. Reliability Engineering & System Safety, 77(2), 143–150. https://doi.org/https://doi.org/10.1016/S0951-8320(02)00041-8