Show simple item record

dc.contributor.authorLombard, F.
dc.contributor.authorVan Zyl, C.
dc.date.accessioned2017-10-10T07:51:35Z
dc.date.available2017-10-10T07:51:35Z
dc.date.issued2018
dc.identifier.citationLombard, F. & Van Zyl, C. 2018. Signed sequential rank CUSUMs. Computational statistics and data analysis, 118:30-39. [https://doi.org/10.1016/j.csda.2017.08.007]en_US
dc.identifier.issn0167-9473
dc.identifier.issn1872-7352 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/25757
dc.identifier.urihttps://doi.org/10.1016/j.csda.2017.08.007
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0167947317301871
dc.description.abstractCUSUMs based on the signed sequential ranks of observations are developed for detecting location and scale changes in symmetric distributions. The CUSUMs are distribution-free and fully self-starting: given a specified in-control median and nominal in-control average run length, no parametric specification of the underlying distribution is required in order to find the correct control limits. If the underlying distribution is normal with unknown variance, a CUSUM based on the Van der Waerden signed rank score produces out-of-control average run lengths that are commensurate with those produced by the standard CUSUM for a normal distribution with known variance. For heavier tailed distributions, use of a CUSUM based on the Wilcoxon signed rank score is indicated. The methodology is illustrated by application to real data from an industrial environmenten_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectCUSUMen_US
dc.subjectDistribution-freeen_US
dc.subjectSelf startingen_US
dc.subjectSigned sequential ranksen_US
dc.subjectSymmetric distributionsen_US
dc.titleSigned sequential rank CUSUMsen_US
dc.typeArticleen_US
dc.contributor.researchID12950149 - Lombard, Frederick


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record