# Posterior Distribution Charts: A Bayesian Approach for Graphically Exploring a Process Mean

@article{Apley2012PosteriorDC, title={Posterior Distribution Charts: A Bayesian Approach for Graphically Exploring a Process Mean}, author={Daniel W. Apley}, journal={Technometrics}, year={2012}, volume={54}, pages={279 - 293} }

We develop a Bayesian approach for monitoring and graphically exploring a process mean and informing decisions related to process adjustment. We assume a rather general model, in which the observations are represented as a process mean plus a random error term. In contrast to previous work on Bayesian methods for monitoring a mean, we allow any Markov model for the mean. This includes a mean that wanders slowly, that is constant over periods of time with occasional random jumps or combinations…

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