An efficient MEWMA chart for Gumbel's bivariate Pareto distribution
Control charts play a vital role in process monitoring to ensure the product's desired standards. Due to rapid improvements in data collection methods, multivariate charts are preferred over univariate charts. This paper proposes a bivariate exponentially weighted moving average chart for the s...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Journal of Taibah University for Science |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/16583655.2024.2338949 |
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| author | Ayesha Talib Sajid Ali Ismail Shah |
| author_facet | Ayesha Talib Sajid Ali Ismail Shah |
| author_sort | Ayesha Talib |
| collection | DOAJ |
| description | Control charts play a vital role in process monitoring to ensure the product's desired standards. Due to rapid improvements in data collection methods, multivariate charts are preferred over univariate charts. This paper proposes a bivariate exponentially weighted moving average chart for the simultaneous monitoring of the mean vector of Gumbel's bivariate Pareto type II (also known as the Lomax distribution) time-between-events data. The performance of the proposed chart is assessed through average run length, median run length, and the standard deviation of the run length criteria. To show the implementation of the chart in the real world, illustrative examples are also presented. |
| format | Article |
| id | doaj-art-8ee6bdf9efe84e51a71e1bd2e2fc3f8c |
| institution | OA Journals |
| issn | 1658-3655 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Taibah University for Science |
| spelling | doaj-art-8ee6bdf9efe84e51a71e1bd2e2fc3f8c2025-08-20T02:36:43ZengTaylor & Francis GroupJournal of Taibah University for Science1658-36552024-12-0118110.1080/16583655.2024.2338949An efficient MEWMA chart for Gumbel's bivariate Pareto distributionAyesha Talib0Sajid Ali1Ismail Shah2Department of Statistics, Quaid-i-Azam University, Islamabad, PakistanDepartment of Statistics, Quaid-i-Azam University, Islamabad, PakistanDepartment of Statistics, Quaid-i-Azam University, Islamabad, PakistanControl charts play a vital role in process monitoring to ensure the product's desired standards. Due to rapid improvements in data collection methods, multivariate charts are preferred over univariate charts. This paper proposes a bivariate exponentially weighted moving average chart for the simultaneous monitoring of the mean vector of Gumbel's bivariate Pareto type II (also known as the Lomax distribution) time-between-events data. The performance of the proposed chart is assessed through average run length, median run length, and the standard deviation of the run length criteria. To show the implementation of the chart in the real world, illustrative examples are also presented.https://www.tandfonline.com/doi/10.1080/16583655.2024.2338949Time-between-eventsbivariate Gumbel distributionEWMA chartaverage run length |
| spellingShingle | Ayesha Talib Sajid Ali Ismail Shah An efficient MEWMA chart for Gumbel's bivariate Pareto distribution Journal of Taibah University for Science Time-between-events bivariate Gumbel distribution EWMA chart average run length |
| title | An efficient MEWMA chart for Gumbel's bivariate Pareto distribution |
| title_full | An efficient MEWMA chart for Gumbel's bivariate Pareto distribution |
| title_fullStr | An efficient MEWMA chart for Gumbel's bivariate Pareto distribution |
| title_full_unstemmed | An efficient MEWMA chart for Gumbel's bivariate Pareto distribution |
| title_short | An efficient MEWMA chart for Gumbel's bivariate Pareto distribution |
| title_sort | efficient mewma chart for gumbel s bivariate pareto distribution |
| topic | Time-between-events bivariate Gumbel distribution EWMA chart average run length |
| url | https://www.tandfonline.com/doi/10.1080/16583655.2024.2338949 |
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