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Control Limits for an Adaptive Self-Starting Distribution-Free CUSUM Based on Sequential Ranks

Lang, Michael (2024)
Control Limits for an Adaptive Self-Starting Distribution-Free CUSUM Based on Sequential Ranks.
In: Technologies, 2019, 7 (4)
doi: 10.26083/tuprints-00015748
Article, Secondary publication, Publisher's Version

Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

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Item Type: Article
Type of entry: Secondary publication
Title: Control Limits for an Adaptive Self-Starting Distribution-Free CUSUM Based on Sequential Ranks
Language: English
Date: 16 January 2024
Place of Publication: Darmstadt
Year of primary publication: 2019
Place of primary publication: Basel
Publisher: MDPI
Journal or Publication Title: Technologies
Volume of the journal: 7
Issue Number: 4
Collation: 19 Seiten
DOI: 10.26083/tuprints-00015748
Corresponding Links:
Origin: Secondary publication DeepGreen

Since their introduction in 1954, cumulative sum (CUSUM) control charts have seen a widespread use beyond the conventional realm of statistical process control (SPC). While off-the-shelf implementations aimed at practitioners are available, their successful use is often hampered by inherent limitations which make them not easily reconcilable with real-world scenarios. Challenges commonly arise regarding a lack of robustness due to underlying parametric assumptions or requiring the availability of large representative training datasets. We evaluate an adaptive distribution-free CUSUM based on sequential ranks which is self-starting and provide detailed pseudo-code of a simple, yet effective calibration algorithm. The main contribution of this paper is in providing a set of ready-to-use tables of control limits suitable to a wide variety of applications where a departure from the underlying sampling distribution to a stochastically larger distribution is of interest. Performance of the proposed tabularized control limits is assessed and compared to competing approaches through extensive simulation experiments. The proposed control limits are shown to yield significantly increased agility (reduced detection delay) while maintaining good overall robustness.

Uncontrolled Keywords: cumulative sums, distribution-free, nonparametric, sequential ranks, change point detection
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-157489
Classification DDC: 000 Generalities, computers, information > 004 Computer science
600 Technology, medicine, applied sciences > 600 Technology
Divisions: Exzellenzinitiative > Graduate Schools > Graduate School of Computational Engineering (CE)
Date Deposited: 16 Jan 2024 12:37
Last Modified: 18 Jan 2024 10:19
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/15748
PPN: 514765593
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