1 |
Mohmoud MA and Maravelakis PE (2013). The performance of multivariate CUSUM control charts with estimated parameters, Journal of Statistical Computation and Simulation, 83, 721-738.
DOI
|
2 |
Montgomery DC (2013). Statistical Quality Control: A Modern Introduction (7th ed), John Wiley & Sons, Singapore.
|
3 |
Nayland College (2004). American new cars and truck, New Zealand.
|
4 |
Nelsen RB (2016). An Introduction to Copulas (2nd ed), Springer, New York.
|
5 |
Niaki STA and Nasaji SA (2011). A hybrid method of artificial neural networks a nd simulated annealing in monitoring auto-correlated multi-attribute processes, International Journal of Advanced Manufacturing Technology, 56, 777-788.
DOI
|
6 |
Patel HI (1973). Quality control methods for multivariate binomial and Poisson distributions, Technometrics, 15, 103-112.
DOI
|
7 |
Petcharat K, Areepong Y, Sukparungsee S, and Mititelu G. (2014). Exact solution for average run length of CUSUM Charts for MA(1) process, Chiang Mai Journal of Science, 41, 1449-1456.
|
8 |
Qiu P (2008). Distribution-free multivariate process control based on log-linear modelling, IIE Transactions, 40, 664-677.
DOI
|
9 |
Rao BV, Disney RL, and Pignatiello JJ (2001). Uniqueness and convergence of solutions to average run length integral equations for cumulative sum and other control charts, IIE Transactions, 33, 463-469.
|
10 |
Runger GC, Keats JB, Montgomery DC, and Scranton RD (1999). Improving the performance of the multivariate exponentially weighted moving average control chart, Quality and reliability of Engineering International, 15, 161-166.
DOI
|
11 |
Shih JH and Louis TA (1995). Inferences on the association parameter in copula models for bivariate survival data, Biometrics, 51, 1384-1399.
DOI
|
12 |
Sklar M (1959). Fonctions de repartition a n dimensions et leurs marges, Publications de l'lnstitut de Statistique de l'Universite de Paris, 8, 229-231.
|
13 |
Sukparungsee S, Kuvattana S, Areepong Y, and Busababodhin P (2016). Bivariate copulas on the exponentially weighted moving average control chart, Songklanakarin Journal of Science and Technology, 38, 569-574.
|
14 |
Suriyakart W, Areepong Y, Sukparungsee S, Mititelu G (2012). Analytical Method of Average Run Length for Trend Exponential AR(1) Processes inEWMA Procedure, IAENG International Journal of Applied Mathematics, 42, 250-253.
|
15 |
Trivedi PK and Zimmer DM (2005). Copula modeling: an introduction for practitioners, Foundations and Trends in Econometrics, 1, 1-111.
DOI
|
16 |
Verdier G (2013). Application of copulas to multivariate control charts, Journal of Statistical Planning and Inference, 143, 2151-2159.
DOI
|
17 |
Xie M and Goh TN (1992). Some procedures for decision making in controlling high yield processes, Quality and Reliability Engineering International, 8, 355-360.
DOI
|
18 |
Xie Y, Xie M, and Goh TN (2011). Two MEWMA charts for Gumbel's bivariate exponential distribution, Journal of Quality Technology, 43, 50-56.
DOI
|
19 |
Zou C and Tsung F (2011). A multivariate sign EWMA control chart, Technometrics, 53, 84-97.
DOI
|
20 |
Alves CC, Samohyl RW, and Henning E (2010). Application of multivariate cumulative sum control charts (MCUSUM) for monitoring a machining process. In Proceedings of the 16th International Conference on Industrial Engineering and Operations Management, Sao Carlos, Brazil.
|
21 |
Bersimis S, Panaretos J, and Psarakis S (2005). Multivariate statistical process control charts and the problem of interpretation: a short overview and some applications in industry. In Proceedings of the 7th Hellenic European Conference on Computer Mathematics and its Applications, Athens, Greece.
|
22 |
Bersimis S, Psarakis S, and Panaretos J (2007). Multivariate statistical process control: an overview, Quality and Reliability Engineering International, 23, 517-543.
DOI
|
23 |
Bourke PD (1991). Detecting shift in fraction nonconforming using run-length control charts with inspection, Journal of Quality Technology, 23, 225-238.
DOI
|
24 |
Busaba J, Sukparungsee S, Areepong Y, and Mititelu G (2012). Analysis of average run length for CUSUM procedure with negative exponential data, Chiang Mai Journal of Science, 39, 200-208.
|
25 |
Genest C and MacKay RJ (1986). The joy of copulas: bivariate distributions with uniform marginals, The American Statistician, 40, 280-283.
|
26 |
Crosier RB (1988). Multivariate generalizations of cumulative sum quality-control schemes, Technometrics, 30, 291-303.
DOI
|
27 |
Dokouhaki P and Noorossana R (2013). A copula Markov CUSUM chart for monitoring the bivariate auto-correlated binary observation, Quality and Reliability Engineering International, 29, 911-919.
DOI
|
28 |
El-Midany TT, El-Baz MA, and Abd-Elwahed MS (2010). A proposed framework for control charts pattern recognition in multivariate procees using artificial neural networks, Expert Systems with Applications, 37, 1035-1042.
DOI
|
29 |
Fatahi AA, Dokouhaki P, and Moghaddam BF (2011). A bivariate control chart based on copula function. In Proceedings of the International Conference on Quality and Reliability (ICQR), Bangkok, Thailand, 292-296.
|
30 |
Fatahi AA, Noorossana R, Dokouhaki P, and Moghaddam BF (2012). Copula-based bivariate ZIP control chart for monitoring rare events, Communications in Statistics - Theory and Methods, 41, 2699-2716.
DOI
|
31 |
Hryniewicz O (2012). On the robustness of the Shewhart control chart to different types of dependencies in data, Frontiers in Statistical Quality Control, 10, 19-33.
|
32 |
Hryniewicz O and Szediw A (2010). Sequential signals on a control chart based on nonparametric statistical tests, Frontiers in Statistical Quality Control, 9, 99-117.
|
33 |
Joe H (1997). Multivariate Models and Dependence Concepts, Chapman & Hall, London.
|
34 |
Joe H (2015). Dependence Modeling with Copulas, CRC Press, Boca Raton, FL.
|
35 |
Kuvattana S, Sukparungsee S, Areepong Y, and Busababodhin P (2016). Bivariate copulas on the exponentially weighted moving average control chart, Songklanakarin Journal of Science and Technology Preprint, 38, 569-574.
|
36 |
Khoo BC, Atta MA, and Phua HN (2009). A study on the performances of MEWMA and MCUSUM charts for skewed distributions. In Proceedings of the 10th Islamic Countries Conference on Statistical Science, Cairo, Egypt, 817-822
|
37 |
Kuvattana S, Sukparungsee S, Areepong Y, and Busababodhin P (2015a). Multivariate control charts for copulas modeling. In S. Ao, A. H. Chan, H. Katagiri, and L. Xu (Eds), IAENG Transactions on Engineering Sciences: Special Issue for the International Association of Engineers Conferences 2015 (pp. 371-381), World Scientific Publishing, Singapore.
|
38 |
Kuvattana S, Sukparungsee S, Busababodhin P, and Areepong Y (2015b). Efficiency of bivariate copulas on the CUSUM chart. In Proceedings of the International Multiconference of Engineers and Computer Scientists (IMECS), Hong Kong.
|
39 |
Larpkiatataworn S (2003). A neural network approach for multi-attribute process control with comparison of two current techniques and guidelines for practical use (Ph.D. Thesis), University of Pittsburgh, PA.
|
40 |
Lowry CA and Montgomery DC (1995). A review of multivariate control charts, IIE Transactions, 27, 800-810.
DOI
|
41 |
Lowry CA,Woodall WH, Champ CW, and Rigdon SE (1992). A multivariate exponentially weighted moving average control chart, Technometrics, 34, 46-53.
DOI
|
42 |
Lu XS (1998). Control chart for multivariate attribute processes, Journal of Production Research, 36, 3477-3489.
DOI
|
43 |
Marcucci M (1985). Monitoring multinomial processes, Journal of Quality Technology, 17, 86-91.
DOI
|