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dc.contributor.authorLombard, F.
dc.contributor.authorHawkins, Douglas M.
dc.contributor.authorPotgieter, Cornelis J.
dc.date.accessioned2017-03-23T11:48:13Z
dc.date.available2017-03-23T11:48:13Z
dc.date.issued2017
dc.identifier.citationLombard, F. et al. 2017. Sequential rank CUSUM charts for angular data. Computational statistics and data analysis, 105:268-279. [https://doi.org/10.1016/j.csda.2016.08.001]en_US
dc.identifier.issn0167-9473
dc.identifier.urihttp://hdl.handle.net/10394/20914
dc.identifier.urihttps://doi.org/10.1016/j.csda.2016.08.001
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0167947316301827
dc.description.abstractA cumulative sum (CUSUM) control chart has desirable properties for checking whether a distribution has changed from an in-control to an out-of-control setting. Distribution-free CUSUMs based on sequential ranks to detect changes in the mean direction and dispersion of angular data are developed and some of their properties are illustrated by theoretical calculations and Monte Carlo simulation. Three applications to sequentially observed angular data from health science, industrial quality control and astrophysics are discusseden_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectAngular dataen_US
dc.subjectCUSUMen_US
dc.subjectSequential ranksen_US
dc.titleSequential rank CUSUM charts for angular dataen_US
dc.typeArticleen_US
dc.contributor.researchID12950149 - Lombard, Frederick


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