New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard Rates
This article is an extension of the Chris-Jerry distribution (C-JD) in that a two-parameter Chris-Jerry distribution (TPCJD) is suggested and its characteristics are studied. Based on the determined domain of attraction and other major statistical properties, the proposed TPCJD seems to fit into the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/15/10/1881 |
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| author | Eberechukwu Q. Chinedu Queensley C. Chukwudum Najwan Alsadat Okechukwu J. Obulezi Ehab M. Almetwally Ahlam H. Tolba |
| author_facet | Eberechukwu Q. Chinedu Queensley C. Chukwudum Najwan Alsadat Okechukwu J. Obulezi Ehab M. Almetwally Ahlam H. Tolba |
| author_sort | Eberechukwu Q. Chinedu |
| collection | DOAJ |
| description | This article is an extension of the Chris-Jerry distribution (C-JD) in that a two-parameter Chris-Jerry distribution (TPCJD) is suggested and its characteristics are studied. Based on the determined domain of attraction and other major statistical properties, the proposed TPCJD seems to fit into the Gumbel domain. Additionally, it has been confirmed that the stress strength is reliable. The tail study suggests that the TPCJD’s substantial tail makes it suited for a range of applications. The study took into account the single acceptance sampling approach using both simulation and real-life situations. The parameters of the TPCJD were estimated by some classical and Bayesian approaches. The mean squared errors (MSE), linear-exponential, and generalized entropy loss functions were deployed to obtain the Bayesian estimators aided by the Markov chain Monte Carlo (MCMC) simulation. An analysis of lifetime data on two events justified the use of the proposed distribution after comparing the results with some standard lifetime models. |
| first_indexed | 2024-03-10T20:52:08Z |
| format | Article |
| id | doaj.art-c7a23b66e6f94abb8c818ff6d26c2655 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-10T20:52:08Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-c7a23b66e6f94abb8c818ff6d26c26552023-11-19T18:18:10ZengMDPI AGSymmetry2073-89942023-10-011510188110.3390/sym15101881New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard RatesEberechukwu Q. Chinedu0Queensley C. Chukwudum1Najwan Alsadat2Okechukwu J. Obulezi3Ehab M. Almetwally4Ahlam H. Tolba5Department of Statistics, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka P.O. Box 5025, Anambra, NigeriaDepartment of Insurance and Risk Management, Faculty of Business Administration, University of Uyo, Akwa P.O. Box 520003, Ibom, NigeriaDepartment of Quantitative Analysis, College of Business Administration, King Saud University, Riyadh 11587, Saudi ArabiaDepartment of Statistics, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka P.O. Box 5025, Anambra, NigeriaDepartment of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi ArabiaDepartment of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, EgyptThis article is an extension of the Chris-Jerry distribution (C-JD) in that a two-parameter Chris-Jerry distribution (TPCJD) is suggested and its characteristics are studied. Based on the determined domain of attraction and other major statistical properties, the proposed TPCJD seems to fit into the Gumbel domain. Additionally, it has been confirmed that the stress strength is reliable. The tail study suggests that the TPCJD’s substantial tail makes it suited for a range of applications. The study took into account the single acceptance sampling approach using both simulation and real-life situations. The parameters of the TPCJD were estimated by some classical and Bayesian approaches. The mean squared errors (MSE), linear-exponential, and generalized entropy loss functions were deployed to obtain the Bayesian estimators aided by the Markov chain Monte Carlo (MCMC) simulation. An analysis of lifetime data on two events justified the use of the proposed distribution after comparing the results with some standard lifetime models.https://www.mdpi.com/2073-8994/15/10/1881Chris-Jerry distributionestimation methodsMarkov chain Monte Carlosingle acceptance sampling planreal data sets |
| spellingShingle | Eberechukwu Q. Chinedu Queensley C. Chukwudum Najwan Alsadat Okechukwu J. Obulezi Ehab M. Almetwally Ahlam H. Tolba New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard Rates Symmetry Chris-Jerry distribution estimation methods Markov chain Monte Carlo single acceptance sampling plan real data sets |
| title | New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard Rates |
| title_full | New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard Rates |
| title_fullStr | New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard Rates |
| title_full_unstemmed | New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard Rates |
| title_short | New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard Rates |
| title_sort | new lifetime distribution with applications to single acceptance sampling plan and scenarios of increasing hazard rates |
| topic | Chris-Jerry distribution estimation methods Markov chain Monte Carlo single acceptance sampling plan real data sets |
| url | https://www.mdpi.com/2073-8994/15/10/1881 |
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