Analysis of a new jointly hybrid censored Rayleigh populations
When a researcher wants to perform a life-test comparison study of items made by two separate lines inside the same institution, joint censoring strategies are particularly important. In this paper, we present a new joint Type-Ⅰ hybrid censoring that enables an experimenter to stop the investigation...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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AIMS Press
2024-01-01
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| Series: | AIMS Mathematics |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/math.2024184?viewType=HTML |
| _version_ | 1797341291134058496 |
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| author | Ahmed Elshahhat Hanan Haj Ahmad Ahmed Rabaiah Osama E. Abo-Kasem |
| author_facet | Ahmed Elshahhat Hanan Haj Ahmad Ahmed Rabaiah Osama E. Abo-Kasem |
| author_sort | Ahmed Elshahhat |
| collection | DOAJ |
| description | When a researcher wants to perform a life-test comparison study of items made by two separate lines inside the same institution, joint censoring strategies are particularly important. In this paper, we present a new joint Type-Ⅰ hybrid censoring that enables an experimenter to stop the investigation as soon as a pre-specified number of failures or time is first achieved. In the context of newly censored data, the estimates of the unknown mean lifetimes of two different Rayleigh populations are acquired using maximum likelihood and Bayesian inferential techniques. The normality characteristic of classical estimators is used to offer asymptotic confidence interval bounds for each unknown parameter. Against gamma conjugate priors, the Bayes estimators and related credible intervals are gathered about symmetric and asymmetric loss functions. Since classical and Bayes estimators are acquired in closed form, simulation tests can be easily made to evaluate the effectiveness of the proposed methodologies. The efficiency of the suggested approaches is examined in terms of four metrics, namely: Root mean squared error, average relative absolute bias, average confidence length, and coverage probability. To demonstrate the applicability of the offered approaches to real events, two real applications employing data sets from the engineering area are analyzed. As a result, when the experimenter's primary goal is to complete the test as soon as the total number of failures or the threshold period is recorded, the numerical results reveal that the recommended strategy is adaptable and very helpful in completing the study. |
| first_indexed | 2024-03-08T10:15:49Z |
| format | Article |
| id | doaj.art-912de3d05fb54a01bd867c90482faf8f |
| institution | Directory Open Access Journal |
| issn | 2473-6988 |
| language | English |
| last_indexed | 2024-03-08T10:15:49Z |
| publishDate | 2024-01-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Mathematics |
| spelling | doaj.art-912de3d05fb54a01bd867c90482faf8f2024-01-29T01:29:23ZengAIMS PressAIMS Mathematics2473-69882024-01-01923740376210.3934/math.2024184Analysis of a new jointly hybrid censored Rayleigh populationsAhmed Elshahhat 0Hanan Haj Ahmad1Ahmed Rabaiah 2Osama E. Abo-Kasem31. Faculty of Technology and Development, Zagazig University, Zagazig 44519, Egypt2. Department of Basic Science, The General Administration of Preparatory Year, King Faisal University, Hofuf 31982, Al Ahsa, Saudi Arabia3. Department of Electrical Engineering, College of Engineering, King Faisal University, Hofuf 31982, Al Ahsa, Saudi Arabia4. Department of Statistics, Faculty of Commerce, Zagazig University, Zagazig 44519, EgyptWhen a researcher wants to perform a life-test comparison study of items made by two separate lines inside the same institution, joint censoring strategies are particularly important. In this paper, we present a new joint Type-Ⅰ hybrid censoring that enables an experimenter to stop the investigation as soon as a pre-specified number of failures or time is first achieved. In the context of newly censored data, the estimates of the unknown mean lifetimes of two different Rayleigh populations are acquired using maximum likelihood and Bayesian inferential techniques. The normality characteristic of classical estimators is used to offer asymptotic confidence interval bounds for each unknown parameter. Against gamma conjugate priors, the Bayes estimators and related credible intervals are gathered about symmetric and asymmetric loss functions. Since classical and Bayes estimators are acquired in closed form, simulation tests can be easily made to evaluate the effectiveness of the proposed methodologies. The efficiency of the suggested approaches is examined in terms of four metrics, namely: Root mean squared error, average relative absolute bias, average confidence length, and coverage probability. To demonstrate the applicability of the offered approaches to real events, two real applications employing data sets from the engineering area are analyzed. As a result, when the experimenter's primary goal is to complete the test as soon as the total number of failures or the threshold period is recorded, the numerical results reveal that the recommended strategy is adaptable and very helpful in completing the study.https://www.aimspress.com/article/doi/10.3934/math.2024184?viewType=HTMLjointly type-ⅰ hybrid censoringrayleigh populationsmaximum likelihoodbayes estimationconfidence intervals |
| spellingShingle | Ahmed Elshahhat Hanan Haj Ahmad Ahmed Rabaiah Osama E. Abo-Kasem Analysis of a new jointly hybrid censored Rayleigh populations AIMS Mathematics jointly type-ⅰ hybrid censoring rayleigh populations maximum likelihood bayes estimation confidence intervals |
| title | Analysis of a new jointly hybrid censored Rayleigh populations |
| title_full | Analysis of a new jointly hybrid censored Rayleigh populations |
| title_fullStr | Analysis of a new jointly hybrid censored Rayleigh populations |
| title_full_unstemmed | Analysis of a new jointly hybrid censored Rayleigh populations |
| title_short | Analysis of a new jointly hybrid censored Rayleigh populations |
| title_sort | analysis of a new jointly hybrid censored rayleigh populations |
| topic | jointly type-ⅰ hybrid censoring rayleigh populations maximum likelihood bayes estimation confidence intervals |
| url | https://www.aimspress.com/article/doi/10.3934/math.2024184?viewType=HTML |
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