A generally weighted moving average exceedance chart

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dc.contributor.author Chakraborty, Niladri
dc.contributor.author Human, Schalk William
dc.contributor.author Balakrishnan, Narayanaswamy
dc.date.accessioned 2018-04-11T06:59:23Z
dc.date.issued 2018-03
dc.description.abstract Distribution-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.department Statistics en_ZA
dc.description.embargo 2019-03-25
dc.description.librarian hj2018 en_ZA
dc.description.sponsorship In 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.uri http://www.tandfonline.com/loi/gscs20 en_ZA
dc.identifier.citation Niladri 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.issn 0094-9655 (print)
dc.identifier.issn 1563-5163 (online)
dc.identifier.other 10.1080/00949655.2018.1447573
dc.identifier.uri http://hdl.handle.net/2263/64482
dc.language.iso en en_ZA
dc.publisher Taylor and Francis en_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.subject Generally weighted moving average (GWMA) en_ZA
dc.subject Nonparametric control chart en_ZA
dc.subject Monte Carlo simulation en_ZA
dc.subject Average run-length en_ZA
dc.subject Precedence statistic en_ZA
dc.subject Exceedance statistic en_ZA
dc.subject GWMA chart en_ZA
dc.title A generally weighted moving average exceedance chart en_ZA
dc.type Postprint Article en_ZA


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