Distribution-free exceedance CUSUM control charts for location
| dc.contributor.author | Mukherjee, A. | |
| dc.contributor.author | Graham, Marien Alet | |
| dc.contributor.author | Chakraborti, Subhabrata | |
| dc.contributor.email | marien.graham@up.ac.za | en_US |
| dc.date.accessioned | 2014-05-19T10:18:16Z | |
| dc.date.available | 2014-05-19T10:18:16Z | |
| dc.date.issued | 2013 | |
| dc.description.abstract | Distribution-free (nonparametric) control charts can be useful to the quality practitioner when the underlying distribution is not known. A Phase II nonparametric CUSUM chart based on the exceedance statistics, called the exceedance CUSUM chart, is proposed here for detecting a shift in the unknown location parameter of a continuous distribution. The exceedance statistics can be more efficient than rank-based methods when the underlying distribution is heavy-tailed and/or right-skewed, which may be the case in some applications, particularly with certain lifetime data. Moreover, exceedance statistics can save testing time and resources as they can be applied as soon as a certain order statistic of the reference sample is available. Guidelines and recommendations are provided for the chart’s design parameters along with an illustrative example. The inand out-of-control performance of the chart are studied through extensive simulations on the basis of the average run-length (ARL), the standard deviation of run-length (SDRL), the median run-length (MDRL) and some percentiles of run-length. Further, a comparison with a number of existing control charts, including the parametric CUSUM X chart and a recent nonparametric CUSUM chart based on the Wilcoxon rank-sum statistic, called the rank-sum CUSUM chart, is made. It is seen that the exceedance CUSUM chart performs well in many cases and thus can be a useful alternative chart in practice. A summary and some concluding remarks are given. | en_US |
| dc.description.librarian | hb2014 | en_US |
| dc.description.uri | http://www.tandfonline.com/loi/lssp20 | en_US |
| dc.identifier.citation | A. Mukherjee , M. A. Graham & S. Chakraborti (2013) Distribution-Free Exceedance CUSUM Control Charts for Location, Communications in Statistics - Simulation and Computation, 42:5, 1153-1187, DOI: 10.1080/03610918.2012.661638 | en_US |
| dc.identifier.issn | 0361-0918 (print) | |
| dc.identifier.issn | 1532-4141 (online) | |
| dc.identifier.other | 10.1080/03610918.2012.661638 | |
| dc.identifier.uri | http://hdl.handle.net/2263/39812 | |
| dc.language.iso | en | en_US |
| dc.publisher | Taylor & Francis | en_US |
| dc.rights | © Taylor & Francis Group, LLC. This is an electronic version of an article published in Communications in Statistics - Simulation and Computation, vol. 42, no. 5, pp. 1153-1187, 2013. doi : http://www.tandfonline.com/loi/lssp20 Communications in Statistics - Simulation and Computation is available online at : http://www.tandfonline.com/loi/lssp20 | en_US |
| dc.subject | Binomial | en_US |
| dc.subject | CUSUM chart | en_US |
| dc.subject | Exceedance statistic | en_US |
| dc.subject | Markov chain | en_US |
| dc.subject | Nonparametric | en_US |
| dc.subject | Precedence statistic | en_US |
| dc.subject | Quality control | en_US |
| dc.subject | Robust | en_US |
| dc.subject | Simulation | en_US |
| dc.title | Distribution-free exceedance CUSUM control charts for location | en_US |
| dc.type | Postprint Article | en_US |
