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A side-sensitive synthetic chart for the multivariate coefficient of variation

Control charts for the coefficient of variations (γ) are receiving increasing attention as it is able to monitor the stability in the ratio of the standard deviation (σ) over the mean (μ), unlike conventional charts that monitor the μ and/or σ separately. A side-sensitive synthetic (SS) chart for mo...

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Autores principales: Yeong, Wai Chung, Lim, Sok Li, Chong, Zhi Lin, Khoo, Michael B. C., Saha, Sajal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9255772/
https://www.ncbi.nlm.nih.gov/pubmed/35788210
http://dx.doi.org/10.1371/journal.pone.0270151
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author Yeong, Wai Chung
Lim, Sok Li
Chong, Zhi Lin
Khoo, Michael B. C.
Saha, Sajal
author_facet Yeong, Wai Chung
Lim, Sok Li
Chong, Zhi Lin
Khoo, Michael B. C.
Saha, Sajal
author_sort Yeong, Wai Chung
collection PubMed
description Control charts for the coefficient of variations (γ) are receiving increasing attention as it is able to monitor the stability in the ratio of the standard deviation (σ) over the mean (μ), unlike conventional charts that monitor the μ and/or σ separately. A side-sensitive synthetic (SS) chart for monitoring γ was recently developed for univariate processes. The chart outperforms the non-side-sensitive synthetic (NSS) γ chart. However, the SS chart monitoring γ for multivariate processes cannot be found. Thus, a SS chart for multivariate processes is proposed in this paper. A SS chart for multivariate processes is important as multiple quality characteristic that are correlated with each other are frequently encountered in practical scenarios. Based on numerical examples, the side-sensitivity feature that is included in the multivariate synthetic γ chart significantly improves the sensitivity of the chart based on the run length performance, particularly in detecting small shifts (τ), and for small sample size (n), as well as a large number of variables (p) and in-control γ (γ(0)). The multivariate SS chart also significantly outperforms the Shewhart γ chart, and marginally outperforms the Multivariate Exponentially Weighted Moving Average (MEWMA) γ chart when shift sizes are moderate and large. To show its implementation, the proposed multivariate SS chart is adopted to monitor investment risks.
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spelling pubmed-92557722022-07-06 A side-sensitive synthetic chart for the multivariate coefficient of variation Yeong, Wai Chung Lim, Sok Li Chong, Zhi Lin Khoo, Michael B. C. Saha, Sajal PLoS One Research Article Control charts for the coefficient of variations (γ) are receiving increasing attention as it is able to monitor the stability in the ratio of the standard deviation (σ) over the mean (μ), unlike conventional charts that monitor the μ and/or σ separately. A side-sensitive synthetic (SS) chart for monitoring γ was recently developed for univariate processes. The chart outperforms the non-side-sensitive synthetic (NSS) γ chart. However, the SS chart monitoring γ for multivariate processes cannot be found. Thus, a SS chart for multivariate processes is proposed in this paper. A SS chart for multivariate processes is important as multiple quality characteristic that are correlated with each other are frequently encountered in practical scenarios. Based on numerical examples, the side-sensitivity feature that is included in the multivariate synthetic γ chart significantly improves the sensitivity of the chart based on the run length performance, particularly in detecting small shifts (τ), and for small sample size (n), as well as a large number of variables (p) and in-control γ (γ(0)). The multivariate SS chart also significantly outperforms the Shewhart γ chart, and marginally outperforms the Multivariate Exponentially Weighted Moving Average (MEWMA) γ chart when shift sizes are moderate and large. To show its implementation, the proposed multivariate SS chart is adopted to monitor investment risks. Public Library of Science 2022-07-05 /pmc/articles/PMC9255772/ /pubmed/35788210 http://dx.doi.org/10.1371/journal.pone.0270151 Text en © 2022 Yeong et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yeong, Wai Chung
Lim, Sok Li
Chong, Zhi Lin
Khoo, Michael B. C.
Saha, Sajal
A side-sensitive synthetic chart for the multivariate coefficient of variation
title A side-sensitive synthetic chart for the multivariate coefficient of variation
title_full A side-sensitive synthetic chart for the multivariate coefficient of variation
title_fullStr A side-sensitive synthetic chart for the multivariate coefficient of variation
title_full_unstemmed A side-sensitive synthetic chart for the multivariate coefficient of variation
title_short A side-sensitive synthetic chart for the multivariate coefficient of variation
title_sort side-sensitive synthetic chart for the multivariate coefficient of variation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9255772/
https://www.ncbi.nlm.nih.gov/pubmed/35788210
http://dx.doi.org/10.1371/journal.pone.0270151
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