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2012 | 892 | 69-78

Article title

Monitorowanie autokorelacyjnego procesu za pomocą łańcuchów Markowa

Title variants

EN
Monitoring Autocorrelated Processes Using the Markov Chain Monte Carlo Method

Languages of publication

PL

Abstracts

EN
The concept of the statistical control chart was developed in 1924 by W. A. Shewhart. The control chart is a graphical display of a quality characteristic such as sample mean, standard deviation or range. The classical control charts are constructed under such assumptions as the form of distribution and independence, and the normality of the distribution is usually assumed. In many situations we may have reason to doubt the validity of the independence assumption – for example, in chemical processes where consecutive measurements on process characteristics are often highly correlated. The paper presents a proposal for a control chart for monitoring auto-correlated processes. The properties of this control chart were analysed in a Monte Carlo study.

Contributors

  • Uniwersytet Ekonomiczny w Katowicach, Katedra Statystyki, ul. 1 Maja 50, 40-287 Katowice, Poland
  • Uniwersytet Ekonomiczny w Katowicach, Katedra Statystyki, ul. 1 Maja 50, 40-287 Katowice, Poland

References

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  • Liu R.Y., Tang J. [1996], Control Chart for Dependent and Independent Measurements Based on Bootstrap Methods, „Journal of the American Statistical Association”, nr 436.
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  • Rayner R.K. [1990], Bootstraping p Values and Power in the First Order Autoregression: A Monte Carlo Investigation, „Journal of Business & Economic Statistics”, vol. 8, nr 2, April.
  • Schmid W., Schöne A. [1997], Some Properties of the EWMA Control Chart in the Presence of Autocorrelation, „The Annals of Statistics”, vol. 25, nr 3.
  • Tang W. [2011], Monitoring Autocorrelated Processes, Open Access Dissertations and Theses, Paper 5670, http://digitalcommons.mcmaster.ca/opendissertations/5670/
  • Zou Ch., Wang Z., Tsung F. [2008], Monitoring Autocorrelated Processes using Variable Sampling Schemes at Fixed-times, „Quality and Reliability Engineering International”, nr 24.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-0d1481ff-b7d6-4874-9ccc-2ca04b47c147
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