Inferences of accelerated generalized type-I hybrid censoring data under power hazard rate population
In reliability engineering or medical studies, more information about the life expectancy of products or materials is needed. This information under use conditions is more difficult to collect especially under highly reliable case. In this paper, the problem of statistical inference when the lifetim...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
|
| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824015734 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846141776618848256 |
|---|---|
| author | Rana A. Bakoban Hanadi M. Abdel-Salam Bakri A. Younis Adel A. Bahaddad Gamal.A. Abd-Elmougod |
| author_facet | Rana A. Bakoban Hanadi M. Abdel-Salam Bakri A. Younis Adel A. Bahaddad Gamal.A. Abd-Elmougod |
| author_sort | Rana A. Bakoban |
| collection | DOAJ |
| description | In reliability engineering or medical studies, more information about the life expectancy of products or materials is needed. This information under use conditions is more difficult to collect especially under highly reliable case. In this paper, the problem of statistical inference when the lifetime of a product or material has the power failure rate distribution is developed. To save the cost and time induced by units the experiment is designed with respect to partially step-stress accelerated life tests (ALTs) with type-I generalized hybrid censoring scheme (GHCS). The point estimate of the model parameters as well as the accelerated factor are obtained with respect to the maximum likelihood (ML) and Bayes methods. Also, the asymptotic normal properties of ML estimates, two bootstrap techniques and Markov Chain Monte Carlo techniques are used to formulate interval estimators. A real lifetime data set is used to illustrate the application of the proposed model. Finally, a Monte Carlo simulation study is constructed to discuss and assess, the proposed model and estimation methods. |
| format | Article |
| id | doaj-art-cddd2bff8eb84b4f89a335d89d8a5125 |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-cddd2bff8eb84b4f89a335d89d8a51252024-12-04T05:12:26ZengElsevierAlexandria Engineering Journal1110-01682025-02-01114353365Inferences of accelerated generalized type-I hybrid censoring data under power hazard rate populationRana A. Bakoban0Hanadi M. Abdel-Salam1Bakri A. Younis2Adel A. Bahaddad3Gamal.A. Abd-Elmougod4Mathematics and Statistics Department, College of Science, University of Jeddah, Jeddah, Saudi ArabiaCollege of Sciences and Human Studies, Prince Mohammad Bin Fahd University, Al-Khobar, Saudi ArabiaDepartment of Mathematics, College of arts and science in Elmgarda, King Khalid University, Saudi ArabiaDepartment of Information System, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Mathematics, Faculty of Science, Islamic University of Madinah, Madinah 42351, Saudi Arabia; Corresponding author.In reliability engineering or medical studies, more information about the life expectancy of products or materials is needed. This information under use conditions is more difficult to collect especially under highly reliable case. In this paper, the problem of statistical inference when the lifetime of a product or material has the power failure rate distribution is developed. To save the cost and time induced by units the experiment is designed with respect to partially step-stress accelerated life tests (ALTs) with type-I generalized hybrid censoring scheme (GHCS). The point estimate of the model parameters as well as the accelerated factor are obtained with respect to the maximum likelihood (ML) and Bayes methods. Also, the asymptotic normal properties of ML estimates, two bootstrap techniques and Markov Chain Monte Carlo techniques are used to formulate interval estimators. A real lifetime data set is used to illustrate the application of the proposed model. Finally, a Monte Carlo simulation study is constructed to discuss and assess, the proposed model and estimation methods.http://www.sciencedirect.com/science/article/pii/S1110016824015734Generalized hybrid censoring schemePower hazard rate distributionAccelerated life testsApproximate normality theoremClassical estimationBayesian estimation |
| spellingShingle | Rana A. Bakoban Hanadi M. Abdel-Salam Bakri A. Younis Adel A. Bahaddad Gamal.A. Abd-Elmougod Inferences of accelerated generalized type-I hybrid censoring data under power hazard rate population Alexandria Engineering Journal Generalized hybrid censoring scheme Power hazard rate distribution Accelerated life tests Approximate normality theorem Classical estimation Bayesian estimation |
| title | Inferences of accelerated generalized type-I hybrid censoring data under power hazard rate population |
| title_full | Inferences of accelerated generalized type-I hybrid censoring data under power hazard rate population |
| title_fullStr | Inferences of accelerated generalized type-I hybrid censoring data under power hazard rate population |
| title_full_unstemmed | Inferences of accelerated generalized type-I hybrid censoring data under power hazard rate population |
| title_short | Inferences of accelerated generalized type-I hybrid censoring data under power hazard rate population |
| title_sort | inferences of accelerated generalized type i hybrid censoring data under power hazard rate population |
| topic | Generalized hybrid censoring scheme Power hazard rate distribution Accelerated life tests Approximate normality theorem Classical estimation Bayesian estimation |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824015734 |
| work_keys_str_mv | AT ranaabakoban inferencesofacceleratedgeneralizedtypeihybridcensoringdataunderpowerhazardratepopulation AT hanadimabdelsalam inferencesofacceleratedgeneralizedtypeihybridcensoringdataunderpowerhazardratepopulation AT bakriayounis inferencesofacceleratedgeneralizedtypeihybridcensoringdataunderpowerhazardratepopulation AT adelabahaddad inferencesofacceleratedgeneralizedtypeihybridcensoringdataunderpowerhazardratepopulation AT gamalaabdelmougod inferencesofacceleratedgeneralizedtypeihybridcensoringdataunderpowerhazardratepopulation |