A generally weighted moving average exceedance chart

dc.contributor.authorChakraborty, Niladri
dc.contributor.authorHuman, Schalk William
dc.contributor.authorBalakrishnan, Narayanaswamy
dc.contributor.emailschalk.human@up.ac.zaen_ZA
dc.date.accessioned2018-04-11T06:59:23Z
dc.date.issued2018-03
dc.description.abstractDistribution-free control charts gained momentum in recent years as they are more efficient in detecting a shift when there is a lack of information regarding the underlying process distribution. However, a distribution-free control chart for monitoring the process location often requires information on the in-control process median. This is somewhat challenging because, in practice, any information on the location parameter might not be known in advance and estimation of the parameter is therefore required. In view of this, a time-weighted control chart, labelled as the Generally Weighted Moving Average (GWMA) exceedance (EX) chart (in short GWMA-EX chart), is proposed for detection of a shift in the unknown process location; this chart is based on exceedance statistic when there is no information available on the process distribution. An extensive performance analysis shows that the proposed GWMA-EX control chart is, in many cases, better than its contenders.en_ZA
dc.description.departmentStatisticsen_ZA
dc.description.embargo2019-03-25
dc.description.librarianhj2018en_ZA
dc.description.sponsorshipIn part by the National Research Foundation of South Africa (Grant Number: 71199) and STATOMET, Department of Statistics, University of Pretoria, South Africa.en_ZA
dc.description.urihttp://www.tandfonline.com/loi/gscs20en_ZA
dc.identifier.citationNiladri Chakraborty, Schalk W. Human & Narayanaswamy Balakrishnan (2018) A generally weighted moving average exceedance chart, Journal of Statistical Computation and Simulation, 88:9, 1759-1781, DOI: 10.1080/00949655.2018.1447573.en_ZA
dc.identifier.issn0094-9655 (print)
dc.identifier.issn1563-5163 (online)
dc.identifier.other10.1080/00949655.2018.1447573
dc.identifier.urihttp://hdl.handle.net/2263/64482
dc.language.isoenen_ZA
dc.publisherTaylor and Francisen_ZA
dc.rights© 2018 Informa UK Limited, trading as Taylor & Francis Group. This is an electronic version of an article published in Journal of Statistical Computation and Simulation, vol. 88, no. 9, pp. 1759-1781, 2018. doi : 10.1080/00949655.2018.1447573. Journal of Statistical Computation and Simulation is available online at : http://www.tandfonline.com/loi/gscs20.en_ZA
dc.subjectGenerally weighted moving average (GWMA)en_ZA
dc.subjectNonparametric control charten_ZA
dc.subjectMonte Carlo simulationen_ZA
dc.subjectAverage run-lengthen_ZA
dc.subjectPrecedence statisticen_ZA
dc.subjectExceedance statisticen_ZA
dc.subjectGWMA charten_ZA
dc.titleA generally weighted moving average exceedance charten_ZA
dc.typePostprint Articleen_ZA

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