Modeling to Engineering and Failure Times Data: Using the Marshall–Olkin Extended Exponential Distribution
In this article, we study and introduce the Marshall–Olkin extended exponential (MO-ExE) distribution, a novel three-parameter life expectancy distribution. The new model is characterized by high adaptability in data analysis. Various mathematical properties, including ordinary moments, moment-gener...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Advances in Mathematical Physics |
| Online Access: | http://dx.doi.org/10.1155/admp/6659119 |
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| Summary: | In this article, we study and introduce the Marshall–Olkin extended exponential (MO-ExE) distribution, a novel three-parameter life expectancy distribution. The new model is characterized by high adaptability in data analysis. Various mathematical properties, including ordinary moments, moment-generating functions (MGFs), and conditional moments (CMs) of the new suggested model, were computed. The model parameters are estimated using the maximum likelihood method. A simulation study is evaluated to demonstrate the behavior of the parameter model. In the final analysis, we demonstrate the significance of the novel model by examining practical data applications, thus, showing the adaptability and potential of the MO-ExE model. |
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| ISSN: | 1687-9139 |