Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis
Accurate estimation techniques are crucial in statistical modeling and reliability analysis, which have significant applications across various industries. The three-parameter Weibull distribution is a widely used tool in this context, but traditional estimation methods often struggle with outliers,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Research
2025
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| Online Access: | http://psasir.upm.edu.my/id/eprint/118535/ http://psasir.upm.edu.my/id/eprint/118535/1/118535.pdf |
| _version_ | 1848867538243420160 |
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| author | Mohd Safari, Muhammad Aslam Masseran, Nurulkamal Abdul Majid, Muhammad Hilmi Mohd Tajuddin, Razik Ridzuan |
| author_facet | Mohd Safari, Muhammad Aslam Masseran, Nurulkamal Abdul Majid, Muhammad Hilmi Mohd Tajuddin, Razik Ridzuan |
| author_sort | Mohd Safari, Muhammad Aslam |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Accurate estimation techniques are crucial in statistical modeling and reliability analysis, which have significant applications across various industries. The three-parameter Weibull distribution is a widely used tool in this context, but traditional estimation methods often struggle with outliers, resulting in unreliable parameter estimates. To address this issue, our study introduces a robust estimation technique for the three-parameter Weibull distribution, leveraging the probability integral transform and specifically employing the Weibull survival function for the transformation, with a focus on complete data. This method is designed to enhance robustness while maintaining computational simplicity, making it easy to implement. Through extensive simulation studies, we demonstrate the effectiveness and resilience of our proposed estimator in the presence of outliers. The findings indicate that this new technique significantly improves the accuracy of Weibull parameter estimates, thereby expanding the toolkit available to researchers and practitioners in reliability data analysis. Furthermore, we apply the proposed method to real-world reliability datasets, confirming its practical utility and effectiveness in overcoming the limitations of existing estimation methodologies in the presence of outliers. |
| first_indexed | 2025-11-15T14:38:05Z |
| format | Article |
| id | upm-118535 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:38:05Z |
| publishDate | 2025 |
| publisher | Nature Research |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1185352025-07-17T03:52:22Z http://psasir.upm.edu.my/id/eprint/118535/ Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis Mohd Safari, Muhammad Aslam Masseran, Nurulkamal Abdul Majid, Muhammad Hilmi Mohd Tajuddin, Razik Ridzuan Accurate estimation techniques are crucial in statistical modeling and reliability analysis, which have significant applications across various industries. The three-parameter Weibull distribution is a widely used tool in this context, but traditional estimation methods often struggle with outliers, resulting in unreliable parameter estimates. To address this issue, our study introduces a robust estimation technique for the three-parameter Weibull distribution, leveraging the probability integral transform and specifically employing the Weibull survival function for the transformation, with a focus on complete data. This method is designed to enhance robustness while maintaining computational simplicity, making it easy to implement. Through extensive simulation studies, we demonstrate the effectiveness and resilience of our proposed estimator in the presence of outliers. The findings indicate that this new technique significantly improves the accuracy of Weibull parameter estimates, thereby expanding the toolkit available to researchers and practitioners in reliability data analysis. Furthermore, we apply the proposed method to real-world reliability datasets, confirming its practical utility and effectiveness in overcoming the limitations of existing estimation methodologies in the presence of outliers. Nature Research 2025-04-03 Article PeerReviewed text en cc_by_nc_nd_4 http://psasir.upm.edu.my/id/eprint/118535/1/118535.pdf Mohd Safari, Muhammad Aslam and Masseran, Nurulkamal and Abdul Majid, Muhammad Hilmi and Mohd Tajuddin, Razik Ridzuan (2025) Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis. Scientific Reports, 15 (1). art. no. 11516. ISSN 2045-2322 https://www.nature.com/articles/s41598-025-96043-1?error=cookies_not_supported&code=2c10ab86-7b02-4ce5-b861-974c90982e4f 10.1038/s41598-025-96043-1 |
| spellingShingle | Mohd Safari, Muhammad Aslam Masseran, Nurulkamal Abdul Majid, Muhammad Hilmi Mohd Tajuddin, Razik Ridzuan Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis |
| title | Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis |
| title_full | Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis |
| title_fullStr | Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis |
| title_full_unstemmed | Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis |
| title_short | Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis |
| title_sort | robust estimation of the three parameter weibull distribution for addressing outliers in reliability analysis |
| url | http://psasir.upm.edu.my/id/eprint/118535/ http://psasir.upm.edu.my/id/eprint/118535/ http://psasir.upm.edu.my/id/eprint/118535/ http://psasir.upm.edu.my/id/eprint/118535/1/118535.pdf |