Identifying the time of polynomial drift in the mean of autocorrelated processes

Quality and Reliability Engineering International

Volumn 26, Issue 5, 2010, Pages 399-415

  Perry, Marcus B ^a  

^a UNIVERSITY OF ALABAMA   (United States)

Author keywords

ARMA(p,q) models; Autocorrelated processes; Change point estimation; Maximum likelihood estimation; Polynomial drift; Stationary processes; Statistical process control (SPC)

Indexed keywords

ARMA(P,Q) MODELS; AUTOCORRELATED PROCESS; CHANGE POINT ESTIMATION; STATIONARY PROCESS; STATISTICAL PROCESS CONTROL (SPC);

AUTOCORRELATION; COMPUTER SIMULATION; CORRELATION DETECTORS; ENGINEERS; ESTIMATION; FLOWCHARTING; MAXIMUM LIKELIHOOD ESTIMATION; MONTE CARLO METHODS; POLYNOMIALS; QUALITY CONTROL;

STATISTICAL PROCESS CONTROL;

EID: 77955692628     PISSN: 07488017     EISSN: 10991638     Source Type: Journal    
DOI: 10.1002/qre.1055     Document Type: Article

References (26)

1. Page ES. Continuous inspection schemes. Biometrika 1954;41:1-9.
2. Nishina K. A comparison of control charts from the viewpoint of changepoint estimation. Quality and Reliability Engineering International 1992;8:537-541.
3. Samuel TR, Pignatiello JJ Jr, Calvin JA. Identifying the time of a step change with Xbar control charts. Quality Engineering 1998;10(3):521-527.
4. Perry MB, Pignatiello JJ Jr, Estimating the change point of a normal process mean with a linear trend disturbance in SPC. Quality Technology and Quantitative Management 2006;3(3):325-334.
5. Perry MB, Pignatiello JJ Jr, A change point model for the location parameter of exponential family densities. IIE Transactions 2008;40(10):947-956.
6. Box G E P, Paniagua-Quinones C. Two charts: Not one. Quality Engineering 2007;19(2):93-100.
7. Nishina K, Wang PH. Performance of CUSUM charts from the viewpoint of change point estimation in the presence of autocorrelation. Quality and Reliability Engineering International 1996;12:3-8.
8. Timmer DH, Pignatiello JJ Jr, Change point estimate for the parameters of an AR (1) process. Quality and Reliability Engineering International 2003;19:355-369.
9. Alwin LC, Roberts HV. Time series modeling for statistical process control. Journal of Business and Economic Statistics 1988;6:87-95.
10. Picard D. Testing and estimating change points in time series. Advances in Applied Probability 1985;12:95-110.
11. Box G E P, Jenkins GM, Reinsel GC. Time Series Analysis: Forecasting and Control. Prentice-Hall: Upper Saddle River, NJ, 1994.
12. Abraham B, Ledolter L. Statistical Methods for Forecasting. Wiley: NY, 1983.
13. del Castillo E. Statistical Process Adjustment for Quality Control. Wiley: NY, 2002.
14. Perry MB, Pignatiello JJ Jr, Identifying the time of step change in the mean of autocorrelated processes. Journal of Applied Statistics; to appear.
15. Zhang NF. A statistical control chart for stationary process data. Technometrics 1998;40:24-38.
16. Mastrangelo CM, Montgomery DC. SPC with correlated observations for the chemical and process industries. Quality and Reliability Engineering International 1995;11(2):79-89.
17. Runger GC, Willemain TR. Model-based and model-free control of autocorrelated processes. Journal of Quality Technology 1995;27:283-292.
18. Lu CW, Reynolds MR. Control charts for monitoring the mean and variance of autocorrelated processes. Journal of Quality Technology 1999;31:259-274.
19. Jiang W, Kwok-Leung T, Woodall WH. A new SPC monitoring method: The ARMA chart. Technometrics 2000;42(4):399-410.
20. Kim S, Alexopoulos A, Tsui K, Wilson JR. A distribution-free tabular CUSUM chart for autocorrelated data. IIE Transactions 2007;39(3):317-330.
21. Montgomery DC. Introduction to Statistical Quality Control (5th edn). Wiley: NY, 2005.
22. Siegmund D. Boundary crossing probabilities and statistical applications. Annals of Statistics 1986;14:361-404.
23. Pignatiello JJ Jr, Samuel TR. Estimation of the change point of a normal process mean in SPC applications. Journal of Quality Technology 2001;33(1):82-95.
24. Box G E P, Cox DR. An analysis of transformations. Journal of the Royal Statistical Society 1964; B26:211-243.
25. Han D, Tsung F. A reference free CUSCORE chart for dynamic mean change detection and a unified framework for charting performance comparison. Journal of the American Statistical Association 2006;101:368-386.
26. Perry MB, Pignatiello JJ Jr, Simpson JR. A magnitude-robust control chart for monitoring and estimating step changes in a Poisson Rate parameter. International Journal of Reliability, Quality and Safety Engineering 2007;14(1):1-20.