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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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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. |
format | Online Article Text |
id | pubmed-9255772 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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