On multivariate control charts
Industrial production requires multivariate control charts to enable monitoring of several components. Recently there has been an increased interest also in other areas such as detection of bioterrorism, spatial surveillance and transaction strategies in finance. In the literature, several types of multivariate counterparts to the univariate Shewhart, EWMA and CUSUM methods have been proposed. We review general approaches to multivariate control chart. Suggestions are made on the special challenges of evaluating multivariate surveillance methods.
|Date of creation:||10 Feb 2011|
|Date of revision:|
|Publication status:||Published as Frisén, Marianne, 'On multivariate control charts' in Producao, 2011, pages 235-241.|
|Contact details of provider:|| Postal: Statistical Research Unit, University of Gothenburg, Box 640, SE 40530 GÖTEBORG|
Web page: http://www.statistics.gu.se/
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- Arthur Yeh & Dennis Lin & Honghong Zhou & Chandramouliswaran Venkataramani, 2003. "A multivariate exponentially weighted moving average control chart for monitoring process variability," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(5), pages 507-536.
- S. Knoth, 2002. "Monitoring the mean and the variance of a stationary process," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 56(1), pages 77-100.
- Clare Marshall & Nicky Best & Alex Bottle & Paul Aylin, 2004. "Statistical issues in the prospective monitoring of health outcomes across multiple units," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(3), pages 541-559.
- Marianne Frisen & Eva Andersson & Linus Schioler, 2010.
"Evaluation of multivariate surveillance,"
Journal of Applied Statistics,
Taylor & Francis Journals, vol. 37(12), pages 2089-2100.
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