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Bayesian quality control for autoregressive moving-average processes. (Chinese. English summary) Zbl 1237.62180

Summary: The aim of this paper is to explore quality control under the condition that the sample data in the autoregressive moving-average processes are not independent, and time series models are introduced to fit these data. Bayesian ARMA control charts are constructed with independent residual series data, and used to monitor the quality in the autocorrelative processes. The results from simulations show that Bayesian ARMA quality control charts can effectively carry out quality control autoregressive moving-average processes, and avoid alarming incorrectly when the processes are under statistical control and alarming when processes are out of control.

MSC:

62P30 Applications of statistics in engineering and industry; control charts
62F15 Bayesian inference
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
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