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...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0270151 |
| _version_ | 1818193847898865664 |
|---|---|
| author | Wai Chung Yeong Sok Li Lim Zhi Lin Chong Michael B C Khoo Sajal Saha |
| author_facet | Wai Chung Yeong Sok Li Lim Zhi Lin Chong Michael B C Khoo Sajal Saha |
| author_sort | Wai Chung Yeong |
| collection | DOAJ |
| 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 (γ0). 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. |
| first_indexed | 2024-12-12T00:52:54Z |
| format | Article |
| id | doaj.art-2f250e013a174a0aac218b41621b96ae |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-12T00:52:54Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-2f250e013a174a0aac218b41621b96ae2022-12-22T00:43:58ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01177e027015110.1371/journal.pone.0270151A side-sensitive synthetic chart for the multivariate coefficient of variation.Wai Chung YeongSok Li LimZhi Lin ChongMichael B C KhooSajal SahaControl 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 (γ0). 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.https://doi.org/10.1371/journal.pone.0270151 |
| spellingShingle | Wai Chung Yeong Sok Li Lim Zhi Lin Chong Michael B C Khoo Sajal Saha A side-sensitive synthetic chart for the multivariate coefficient of variation. PLoS ONE |
| 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 |
| url | https://doi.org/10.1371/journal.pone.0270151 |
| work_keys_str_mv | AT waichungyeong asidesensitivesyntheticchartforthemultivariatecoefficientofvariation AT soklilim asidesensitivesyntheticchartforthemultivariatecoefficientofvariation AT zhilinchong asidesensitivesyntheticchartforthemultivariatecoefficientofvariation AT michaelbckhoo asidesensitivesyntheticchartforthemultivariatecoefficientofvariation AT sajalsaha asidesensitivesyntheticchartforthemultivariatecoefficientofvariation AT waichungyeong sidesensitivesyntheticchartforthemultivariatecoefficientofvariation AT soklilim sidesensitivesyntheticchartforthemultivariatecoefficientofvariation AT zhilinchong sidesensitivesyntheticchartforthemultivariatecoefficientofvariation AT michaelbckhoo sidesensitivesyntheticchartforthemultivariatecoefficientofvariation AT sajalsaha sidesensitivesyntheticchartforthemultivariatecoefficientofvariation |