| Autor: |
Mustapha Muhammad, Badamasi Abba, Jinsen Xiao, Najwan Alsadat, Farrukh Jamal, Mohammed Elgarhy |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 12, Pp 156235-156251 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3485219 |
| Popis: |
This paper introduces a novel Poisson-unit-Weibull (PUW) distribution, which is defined on a unit domain and characterized by three parameters. The PUW distribution is capable of accommodating diverse non-monotone failure rates. The paper explores several significant statistical properties of the model, including the explicit closed-form expressions for the $r^{th}$ moments, quantile function, and Shannon entropy. The parameters of the PUW distribution are estimated using maximum likelihood estimation (MLE) and Bayes estimation with a square error loss function. The performance of these estimation methods is evaluated through Monte Carlo simulation studies. Furthermore, the paper discusses the practical aspects of the PUW-quantile regression model and its MLE, employing residual analysis in simulation studies. The flexibility of the PUW and PUW-quantile regression model is demonstrated through six real-life applications, showcasing their superior performance when compared to other popularly used models. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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