- [1] Kamranrad, R, Amiri, A, Niaki, STA. New Approaches in Monitoring Multivariate Categorical Processes based on Contingency Tables in Phase II. Quality and Reliability Engineering International. 2017; 33(5): 1105-1129.
- [2] Subramanyam K, Rao, MB. Analysis of odds ratios in 2×n ordinal contingency tables. Multivariate Statistics and Probability. 1989; 27(1): 505-520.
- [3] Beh, EJ, Davy, PJ. Theory & Methods: Partitioning Pearson’s Chi‐Squared Statistic for a Completely Ordered Three‐Way Contingency Table. Australian & New Zealand Journal of Statistics.1998;40(4):465-477.
- [4] Zafar, S. Non-iterative Estimation Methods for Ordinal Log-linear Models. Doctoral dissertation, The University of Newcastle; 2017.
- [5] Yamamoto, K, Murakami, H. Model based on skew normal distribution for square contingency tables with ordinal categories. Computational Statistics & Data Analysis. 2014;78(1):135-140.
- [6] Brzezińska, J. Ordinal Log-Linear Models for Contingency Tables. Folia Oeconomica Stetinensia, 2016;16(1):264-273.
- [7] Soleymanian, ME, Khedmati, M, Mahlooji, H. Phase II monitoring of binary response profiles. Scientia Iranica Transaction E, Industrial Engineering. 2013;20(6):2238-2246.
- [8] Atashgar, K. Monitoring multivariate environments using artificial neural network approach: An overview. Scientia Iranica Transaction E, Industrial Engineering. 2015;22(6):2527-2547.
- [9] Zolfaghari, S, Amiri, A. Monitoring multivariate-attribute quality characteristics in two stage processes using discriminant analysis based control charts. Scientia Iranica Transaction E, Industrial Engineering. 2016;23(2):757-767.
- [10] Ghashghaei, R, Amiri, A. Maximum multivariate exponentially weighted moving average and maximum multivariate cumulative sum control charts for simultaneous monitoring of mean and variability of multivariate multiple linear regression profiles. Scientia Iranica Transaction E, Industrial Engineering. 2017;24(5):2605-2622.
- [11] Zhen, X, Basawa IV. Categorical time series models for contingency tables. Statistics & Probability Letters. 2009;79(10):1331-1336.
- [12] Ghoreishi, SK, Alijani, M. Dynamic association modeling in 2× 2 contingency tables. Statistical Methodology. 2011;8(2):242-255.
- [13] Kieffer, D, Bianchetti, L, Poch, O. Wicker N. Perfect sampling on 2×⋯× 2× K contingency tables with an application to SAGE data. Journal of Statistical Planning and Inference. 2012;142(4):896-901.
- [14] Kijima, S, Matsui T. Polynomial time perfect sampling algorithm for two‐rowed contingency tables. Random Structures & Algorithms. 2006;29(2):243-256.
- [15] Yashchin On detection of changes in categorical data. Quality Technology & Quantitative Management. 2012;9(1):79-96.
- [16] Li, J, Tsung F, Zou C. Directional control schemes for multivariate categorical processes. Journal of Quality Technology. 2012;44(2):136-154.
- [17] Li, Z, Zou C, Wang Z, Huwang L. A multivariate sign chart for monitoring process shape parameters. Journal of Quality Technology. 2013;45(2):149-165.
- [18] Li, J, Tsung, F, Zou, C. Multivariate binomial/multinomial control chart. IIE Transactions. 2014;46(5):526-542.
- [19] Kamranrad, R, Amiri, A, Niaki, STA. Phase-II monitoring and diagnosing of multivariate categorical processes using generalized linear test-based control charts. Communications in Statistics-Simulation and Computation. 2017;46(8):5951-5980.
- [20] Li J, Tsung F, Zou C. Directional change‐point detection for process control with multivariate categorical data. Naval Research Logistics (NRL). 2013;60(2):160-173.
- [21] Kamranrad R, Amiri A, Niaki STA. Phase‐I monitoring of log‐linear model‐based processes (a case study in health care: Kidney patients). Quality and Reliability Engineering International. 2019;35(6):1766-1788.
- [22] Li, J, Tsung F, Zou C. A simple categorical chart for detecting location shifts with ordinal information. International Journal of Production Research. 2014; 52(2):550-562.
- [23] Perry, M. An EWMA control chart for categorical processes with applications to social network monitoring. Journal of Quality Technology, 2020; 52(2): 182-197.
- [24] Li, W, Zhang C, Tsung F, Mei Y. Nonparametric monitoring of multivariate data via KNN learning. International Journal of Production Research, 2021;59(20): 6311-6326.
- [25] Xiang, D, Pu X, Ding, D, Liang W. An efficient charting scheme for multivariate categorical process with a sparse contingency table. Journal of Quality Technology, 2021;53(1): 88-105.
- [26] Wang, J, Li J, Su, Q. Multivariate ordinal categorical process control based on log-linear modeling. Journal of Quality Technology, 2017;49(2): 108-122.
- [27] Hakimi, A, Farughi, H, Amiri, A, Arkat J. New phase II control chart for monitoring ordinal contingency table based processes. Journal of Industrial and Systems Engineering, 2019; 12(Statistical Processes and Statistical Modeling): 15-34.
- [28] Agresti, A. Categorical Data Analysis. Department of Statistics University of Florida Gainesville, Florida: John Wiley & Sons, Inc., Hoboken, New Jersey; 2002.
Agresti, A. Analysis of ordinal categorical data. Department of Statistics University of Florida Gainesville, Florida: John Wiley & Sons, Inc., Hoboken, New Jersey; 2010.
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