A nonparametric change point model for multivariate phase-II statistical process control.

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A nonparametric change point model for multivariate phase-II statistical process control.

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2011-05

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Phase-II statistical process control (SPC) procedures are designed to detect a change in distribution when a possibly never-ending stream of observations is collected. Extensive study has been conducted with the purpose of detecting a shift in location (e.g. mean or median) when univariate observations are collected. Many techniques have also been proposed to detect a shift in location vector when each observation consists of multiple measurements. These procedures require the user to make assumptions about the distribution of the process readings, to assume that process parameters are known, or to collect a large training sample before monitoring the ongoing process for a change in distribution. We propose a nonparametric procedure for multivariate phase-II statistical process control that does not require the user to make strong assumptions, or to collect a large training sample before monitoring the process for a shift in location vector.

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University of Minnesota Ph.D. dissertation. May 2011. Major:Statistics. Advisor: Douglas M. Hawkins. 1 computer file (PDF); x, 107 pages, appendices p. 104-107.

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Holland, Mark David. (2011). A nonparametric change point model for multivariate phase-II statistical process control.. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/107843.

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