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Using the predictive distribution to determine control limits for the Bayesian MEWMA chart
Authors:Steven E Rigdon  William H Woodall
Institution:1. Department of Biostatistics, Saint Louis University, St. Louis, MO, USA;2. Department of statistics, Virginia Tech, Blacksburg, VA, USA
Abstract:Bayesian control charts have been proposed for monitoring multivariate processes with the multivariate exponentially weighted moving average (MEWMA) statistic. It has been suggested that we use limits based on the predictive distribution of the MEWMA statistic. This analysis, however is based on the erroneous result that the average run length (ARL) is a function of the exceedance probability, that is, the probability that the first point exceeds the control limit. We show how this result can be corrected and we discuss how the Bayesian MEWMA chart with limits based on the predictive distribution compares with other multivariate control chart procedures.
Keywords:Bayesian  Parameter estimation  Phase I  Statistical process monitoring
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