On a New Modification of the Weibull Model with Classical and Bayesian Analysis
Modelling data in applied areas particularly in reliability engineering is a prominent research topic. Statistical models play a vital role in modelling reliability data and are useful for further decision-making policies. In this paper, we study a new class of distributions with one additional shap...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5574112 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850233017954467840 |
|---|---|
| author | Yen Liang Tung Zubair Ahmad Omid Kharazmi Clement Boateng Ampadu E.H. Hafez Sh. A.M. Mubarak |
| author_facet | Yen Liang Tung Zubair Ahmad Omid Kharazmi Clement Boateng Ampadu E.H. Hafez Sh. A.M. Mubarak |
| author_sort | Yen Liang Tung |
| collection | DOAJ |
| description | Modelling data in applied areas particularly in reliability engineering is a prominent research topic. Statistical models play a vital role in modelling reliability data and are useful for further decision-making policies. In this paper, we study a new class of distributions with one additional shape parameter, called a new generalized exponential-X family. Some of its properties are taken into account. The maximum likelihood approach is adopted to obtain the estimates of the model parameters. For assessing the performance of these estimators, a comprehensive Monte Carlo simulation study is carried out. The usefulness of the proposed family is demonstrated by means of a real-life application representing the failure times of electronic components. The fitted results show that the new generalized exponential-X family provides a close fit to data. Finally, considering the failure times data, the Bayesian analysis and performance of Gibbs sampling are discussed. The diagnostics measures such as the Raftery–Lewis, Geweke, and Gelman–Rubin are applied to check the convergence of the algorithm. |
| format | Article |
| id | doaj-art-0d73bcd2ccb44769a071246bf3b7ce3d |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-0d73bcd2ccb44769a071246bf3b7ce3d2025-08-20T02:03:00ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55741125574112On a New Modification of the Weibull Model with Classical and Bayesian AnalysisYen Liang Tung0Zubair Ahmad1Omid Kharazmi2Clement Boateng Ampadu3E.H. Hafez4Sh. A.M. Mubarak5Accounting Department, School of Business, Nanjing University, Nanjing 210093, ChinaDepartment of Statistics, Yazd University, P.O. Box 89175-741,, Yazd, IranDepartment of Statistics, Faculty of Sciences, Vali-e-Asr University of Rafsanjan, Rafsanjan, IranDepartment of Mathematics, Central Michigan University, Mt Pleasant 48859, MI, USADepartment of Mathematics, Faculty of Science, Helwan University, Cairo, EgyptHigh Institute of Engineering and Technology, Ministry of Higher Education, El-Minia, EgyptModelling data in applied areas particularly in reliability engineering is a prominent research topic. Statistical models play a vital role in modelling reliability data and are useful for further decision-making policies. In this paper, we study a new class of distributions with one additional shape parameter, called a new generalized exponential-X family. Some of its properties are taken into account. The maximum likelihood approach is adopted to obtain the estimates of the model parameters. For assessing the performance of these estimators, a comprehensive Monte Carlo simulation study is carried out. The usefulness of the proposed family is demonstrated by means of a real-life application representing the failure times of electronic components. The fitted results show that the new generalized exponential-X family provides a close fit to data. Finally, considering the failure times data, the Bayesian analysis and performance of Gibbs sampling are discussed. The diagnostics measures such as the Raftery–Lewis, Geweke, and Gelman–Rubin are applied to check the convergence of the algorithm.http://dx.doi.org/10.1155/2021/5574112 |
| spellingShingle | Yen Liang Tung Zubair Ahmad Omid Kharazmi Clement Boateng Ampadu E.H. Hafez Sh. A.M. Mubarak On a New Modification of the Weibull Model with Classical and Bayesian Analysis Complexity |
| title | On a New Modification of the Weibull Model with Classical and Bayesian Analysis |
| title_full | On a New Modification of the Weibull Model with Classical and Bayesian Analysis |
| title_fullStr | On a New Modification of the Weibull Model with Classical and Bayesian Analysis |
| title_full_unstemmed | On a New Modification of the Weibull Model with Classical and Bayesian Analysis |
| title_short | On a New Modification of the Weibull Model with Classical and Bayesian Analysis |
| title_sort | on a new modification of the weibull model with classical and bayesian analysis |
| url | http://dx.doi.org/10.1155/2021/5574112 |
| work_keys_str_mv | AT yenliangtung onanewmodificationoftheweibullmodelwithclassicalandbayesiananalysis AT zubairahmad onanewmodificationoftheweibullmodelwithclassicalandbayesiananalysis AT omidkharazmi onanewmodificationoftheweibullmodelwithclassicalandbayesiananalysis AT clementboatengampadu onanewmodificationoftheweibullmodelwithclassicalandbayesiananalysis AT ehhafez onanewmodificationoftheweibullmodelwithclassicalandbayesiananalysis AT shammubarak onanewmodificationoftheweibullmodelwithclassicalandbayesiananalysis |