Robustness of the EWMA control chart for individual observations

dc.contributor.authorHuman, Schalk William
dc.contributor.authorKritzinger, Pierre
dc.contributor.authorChakraborti, Subhabrata
dc.contributor.emailschalk.human@up.ac.zaen_US
dc.date.accessioned2012-05-02T08:48:01Z
dc.date.available2012-10-31T00:20:03Z
dc.date.issued2011-10
dc.description.abstractThe traditional exponentially weighted moving average (EWMA) chart is one of the most popular control charts used in practice today. The in-control robustness is the key to the proper design and implementation of any control chart, lack of which can render its out-of-control shift detection capability almost meaningless. To this end, Borror et al. [5] studied the performance of the traditional EWMA chart for the mean for i.i.d. data. We use a more extensive simulation study to further investigate the in-control robustness (to non-normality) of the three different EWMA designs studied by Borror et al. [5]. Our study includes a much wider collection of non-normal distributions including light- and heavy-tailed and symmetric and asymmetric bi-modal as well as the contaminated normal, which is particularly useful to study the effects of outliers. Also, we consider two separate cases: (i) when the process mean and standard deviation are both known and (ii) when they are both unknown and estimated from an in-control Phase I sample. In addition, unlike in the study done by Borror et al. [5], the average run-length (ARL) is not used as the sole performance measure in our study, we consider the standard deviation of the run-length (SDRL), the median run-length (MDRL), and the first and the third quartiles as well as the first and the 99th percentiles of the in-control run-length distribution for a better overall assessment of the traditional EWMA chart’s in-control performance. Our findings sound a cautionary note to the (over) use of the EWMA chart in practice, at least with some types of non-normal data. A summary and recommendations are provided.en
dc.description.librariannf2012en
dc.description.sponsorshipSTATOMET and the Department of Statistics at the University of Pretoria.en_US
dc.description.urihttp://www.tandfonline.com/loi/cjas20en_US
dc.identifier.citationHuman, SW, Kritzinger, P & Chakraborti, S 2011, 'Robustness of the EWMA control chart for individual observations', Journal of Applied Statistics, vol. 38, no. 10, pp. 2071-2087.en
dc.identifier.issn0266-4763 (print)
dc.identifier.issn1360-0532 (online)
dc.identifier.other10.1080/02664763.2010.545114
dc.identifier.urihttp://hdl.handle.net/2263/18650
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.rights© 2011 Taylor & Francis. This is an electronic version of an article published in Journal of Applied Statistics, vol. 38, no. 10, pp. 2071-2087, October 2011. Journal of Applied Statistics is available online at: http://www.tandfonline.com/loi/cjas20.en_US
dc.subjectAverage run-lengthen
dc.subjectBox-plotsen
dc.subjectDistribution-free statisticsen
dc.subjectMedian run-lengthen
dc.subjectPercentilesen
dc.subjectEWMA control charten
dc.subject.lcshNonparametric statisticsen
dc.subject.lcshProcess control -- Statistical methodsen
dc.subject.lcshStatistics -- Simulation methodsen
dc.subject.lcshRobust controlen
dc.titleRobustness of the EWMA control chart for individual observationsen
dc.typePostprint Articleen

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