PERTANIKA JOURNAL OF TROPICAL AGRICULTURAL SCIENCE

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• Calzada, M. E., & Scariano, S. M. (2013). A synthetic control chart for the coefficient of variation. Journal of Statistical Computation and Simulation, 83(5), 853-867. https://doi.org/10.1080/00949655.2011.639772

• Castagliola, P., Achouri, A., Taleb, H., Celano, G., & Psarakis, S. (2013). Monitoring the coefficient of variation using control charts with run rules. Quality Technology and Quantitative Management, 10(1), 75-94. https://doi.org/10.1080/16843703.2013.11673309

• Castagliola, P., Celano, G., & Psarakis, S. (2011). Monitoring the coefficient of variation using EWMA charts. Journal of Quality Technology, 43(3), 249-265. https://doi.org/10.1080/00224065.2011.11917861

• Curto, J. D., & Pinto, J. C. (2009). The coefficient of variation asymptotic distribution in the case of non-iid random variables. Journal of Applied Statistics, 36(1), 21-32. https://doi.org/10.1080/02664760802382491

• Davis, R. B., & Woodall, W. H. (2002). Evaluating and improving the synthetic control chart. Journal of Quality Technology, 34(2), 200-208. https://doi.org/10.1080/00224065.2002.11980146

• Kang, C. W., Lee, M. S., Seong, Y. J., & Hawkins, D. M. (2007). A control chart for the coefficient of variation. Journal of Quality Technology, 39(2), 151-158. https://doi.org/10.1080/00224065.2007.11917682

• Khan, Z., Razali, R. B., Daud, H., Nor, N. M., & Fotuhi-Firuzabad, M. (2017). The control chart technique for the detection of the problem of bad data in state estimation power system. Pertanika Journal of Science & Technology, 25(3), 825-834.

• Kinat, S., Amin, M., & Mahmood, T. (2020). GLM-based control charts for the inverse Gaussian distributed response variable. Quality and Reliability Engineering International, 36(2), 765-783. https://doi.org/10.1002/qre.2603

• Knoth, S. (2016). The case against the use of the synthetic control charts. Journal of Quality Technology, 48(2), 178-195. https://doi.org/10.1080/00224065.2016.11918158

• Machado, M. A. G., & Costa, A. F. B. (2014). Some comments regarding the synthetic chart. Communications in Statistics - Theory and Methods, 43(14), 2897-2906. https://doi.org/10.1080/03610926.2012.683128

• Mahmood, T., & Abbasi, S. A. (2021). Efficient monitoring of coefficient of variation with an application to chemical reactor process. Quality and Reliability Engineering International, 37(3), 1135-1149. https://doi.org/10.1002/qre.2785

• Marchant, C., Leiva, V., Cysneiros, F. J. A., & Liu, S. (2018). Robust multivariate control charts based on Birnbaum-Saunders distributions. Journal of Statistical Computation and Simulation, 88(1), 182-202. https://doi.org/10.1080/00949655.2017.1381699

• Mim, F. N., Saha, S., Khoo, M. B. C., & Khatun, M. (2019). A side-sensitive modified group runs control chart with auxiliary information to detect process mean shifts. Pertanika Journal of Science & Technology, 27(2), 847-866.

• Montgomery, D. C. (2019). Introduction to statistical quality control. John Wiley and Sons Inc.

• Pang, W. K., Yu, B. W., Troutt, M. D., & Shui, H. H. (2008). A simulation-based approach to the study of coefficient of variation of dividend yields. European Journal of Operational Research, 189(2), 559-569. https://doi.org/10.1016/j.ejor.2007.05.032

• Rakitzis, A. C., Chakraborti, S., Shongwe, S. C., Graham, M. A., & Khoo, M. B. C. (2019). An overview of synthetic-type control charts: Techniques and methodology. Quality and Reliability Engineering International, 35(7), 2081-2096. https://doi.org/10.1002/qre.2491

• Shongwe, S. C., & Graham, M. A. (2017). A letter to the editor about “Machado, MAG and Costa AFB (2014), some comments regarding the synthetic chart. Communications in Statistics---Theory and Methods, 43 (14), 2897–2906”. Communications in Statistics - Theory and Methods, 46(21), 10476-10480. https://doi.org/10.1080/03610926.2016.1236958

• Shongwe, S. C., & Graham, M. A. (2019). Some theoretical comments regarding the run-length properties of the synthetic and runs-rules X¯ monitoring schemes–part 2: Steady-state. Quality Technology & Quantitative Management, 16(2), 190-199. https://doi.org/10.1080/16843703.2017.1389141

• Teoh, W. L., Khoo, M. B. C., Yeong, W. C., & Teh, S. Y. (2016). A comparison between the performances of synthetic and EWMA charts for monitoring the coefficient of variation. Journal of Scientific Research and Development, 3(1), 16-20.

• Wu, Z., & Spedding, T. A. (2000). A synthetic control chart for detecting small shifts in the process mean. Journal of Quality Technology, 32(1), 32-38. https://doi.org/10.1080/00224065.2000.11979969

• Wu, Z., Ou, Y., Castagliola, P., & Khoo, M. B. C. (2010). A combined synthetic & X chart for monitoring the process mean. International Journal of Production Research, 48(24), 7423-7436. https://doi.org/10.1080/00207540903496681

• Yeong, W. C., Khoo, M. B. C., Tham, L. K., Teoh, W. L., & Rahim, M. A. (2017). Monitoring the coefficient of variation using a variable sampling interval EWMA chart. Journal of Quality Technology, 49(4), 380-401. https://doi.org/10.1080/00224065.2017.11918004

• Yeong, W. C., Lim, S. L., Khoo, M. B. C., Chuah, M. E., & Lim, A. J. X. (2018). The economic and economic-statistical designs of the synthetic chart for the coefficient of variation. Journal of Testing and Evaluation, 46(3), 1175-1195. https://doi.org/10.1520/JTE20160500

• You, H. W. (2018). Design of the side sensitive group runs chart with estimated parameters based on expected average run length. Pertanika Journal of Science & Technology, 26(3), 847-866.

• Zhang, J., Li, Z., & Wang, Z. (2018). Control chart for monitoring the coefficient of variation with an exponentially weighted moving average procedure. Quality and Reliability Engineering International, 34(2), 188-202. https://doi.org/10.1002/qre.2247