[1] Hotelling, H. (1947). Multivariate quality control. In: Techniques of statistical analysis. McGraw-Hill, New York.
[2] Montgomery, D. C. (1996). Introduction to statistical quality control. John Wiley & Sons Inc., USA.
[3] Liu, R. Y., Parelius, J., & Singh, K. (1999). Multivariate Analysis by Data Depth: Descriptive Statistics, Graphics and Inference (with discussion). Annals of Statistics, 27, 783-858.
[4] Li, J., & Liu, R. Y. (2004). New Nonparametric Tests of Multivariate Locations and Scales Using Data Depth. Statistical Science, 19(4), 686-696.
[5] Vencalek, O. (2011). Concept of Data Depth and its Applications. Acta Universitatis Palackianae Olomucensis, Facultas Rerum Naturalium, Mathematica, 50, 111-119.
[6] Shirke, D., & Khorate, S. (2017). Power Comparison of Data Depth-Based Nonparametric Tests for Testing Equality of Locations. Journal of Statistical Computation and Simulation, 87(8), 1489-1497.
[7] Dehghan, S., & Faridrohani, M. R. (2018). Affine Invariant Depth-Based Tests for the Multivariate One-Sample Location Problem. TEST, 28(3), 671-693.
[8] Barale, M. S., & Shirke, D. T. (2019). Nonparametric Control Charts Based on Data Depth for Location Parameter. Journal of Statistical Theory and Practice, 13(3), 41.
[9] Liu, R. Y. (1995). Control Charts for Multivariate Processes. Journal of the American Statistical Association, 90, 1380-1387.
[10] Hamurkaroglu, C., Mert, M., & Saykan, Y. (2004). Nonparametric Control Charts Based on Mahalanobis Depth. Hacettepe Journal of Mathematics and Statistics, 33, 57-67.
[11] Bae, S. J., Do, G., & Kvam, P. (2016). On Data Depth and the Application of Nonparametric Multivariate Statistical Process Control Charts. Applied Stochastic Models in Business and Industry, 32(5), 660-676.
[12] Czabak-Gorska, I. D. (2018). Multivariate Control Charts Based on Data Depth for Subgroup Location and Scale. CBU International Conference on Innovations in Science and Education, 1042-1049.
[13] Faraz, A., Saniga, E., & Montgomery, D. (2019). Percentile‐Based Control Chart Design with an Application to Shewhart X̅ and Control Charts. Quality and Reliability Engineering International, 35(1), 116-126.
[14] Montgomery, D. C. (2013). Introduction to statistical quality control. 7th ed. Hoboken, NJ: John Wiley & Sons.
[15] Gan, F. F. (2013). An Optimal Design of EWMA Control Charts Based on Median Run Length. Journal of Statistical Computation and Simulation, 45, 169-184.
[16] Gan, F. F. (1994). An Optimal Design of Cumulative Sum Control Chart Based on Median Run Length. Communication in Statistics- Simulation and Computation, 23(2), 485-503.
[17] Chakraborti, S. (2007). Run Length Distribution and Percentiles: The Shewhart X Chart with Unknown Parameters. Quality Engineering, 19(2), 119-127.
[18] Golosnoy, V., & Schmid, W. (2007). EWMA Control Charts for Monitoring Optimal Portfolio Weights. Sequential Analysis (Design Methods and Applications), 26(2), 195-224.
[19] Das, N. (2009). A Comparison Study of Three Non-parametric Control Charts to Detect Shift in Location Parameters. The International Journal of Advanced Manufacturing Technology, 41(7-8), 799-807.
[20] Khoo, M. B. C., Wong, V. H., Wu, Z., & Castagliola, P. (2012). Optimal Design of the Synthetic Chart for the Process Mean Based on Median Run Length. IIE Transactions, 44(9), 765-779.
[21] Khoo, M. B. C., Wong, V. H., Wu, Z., & Castagliola, P. (2011). Optimal Design of the Multivariate Synthetic Chart for Monitoring the Process Mean Vector Based on Median Run Length. Quality and Reliability Engineering International, 27(8), 979-1234.
[22] Zuo, Y., Serfling, R. J. (2000). General Notions of Statistical Depth Function. Annals of Statistics, 28(2), 461-482.
[23] Liu, R.Y., Singh, K. (1993). A Quality Index Based on Data Depth and Multivariate Rank Tests. Journal of the American Statistical Association, 88(421), 252-260.
[24] Haupt, R. L., Haupt, S. E., Haupt S. E. (1998). Practical Genetic Algorithms. 2 New york, Wiley