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QICID: 30616
Title: A CUSUM Chart for Monitoring a Proportion with Autocorrelated Binary Observations
Copyright: ASQ
Author: Mousavi, Shabnam; Reynolds, Marion R., Jr.
Organization: Georgia State University; Max Planck Institute for Human Development; Virginia Tech
Subject: Cumulative sum control chart (CUSUM); Bernoulli trials; Process analysis; Parameters; Markov chains; Sample size; Monitoring;
Series: Journal of Quality Technology, Vol. 41, No. 4, September 2009, pp. 401-414
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Abstract: [This abstract is based on the authors' abstract.]
When monitoring a proportion ρ with conventional control charts, it is assumed that the binary observations are independent. However, the observations from many processes are autocorrelated, and this can have an adverse effect on the performance of the charts. The problem of monitoring ρ is investigated when there is a continuous stream of binary observations that follow a two-state Markov chain model with first order dependence. A Markov binary CUSUM chart is constructed based on a log-likelihood-ratio statistic. Results show this chart can detect most increases in ρ faster than competing charts. The effect of the size of the Phase I data set used in constructing the proposed chart is also discussed.
Number of pages: 14
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