On a new PGDUS transformed model using Inverse Weibull distribution
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866909582059634688 |
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| author | Gauthami, P Chacko, V M |
| author_facet | Gauthami, P Chacko, V M |
| contents | The Power Generalized DUS (PGDUS) Transformation is significant in reliability theory, especially for analyzing parallel systems. From the Generalized Extreme Value distribution, Inverse Weibull model particularly has wide applicability in statistics and reliability theory. In this paper we consider PGDUS transformation of Inverse Weibull distribution. The basic statistical characteristics of the new model are derived, and unknown parameters are estimated using Maximum likelihood and Maximum product of spacings methods. Simulation analysis and the reliability parameter P(T2 < T1) are explored. The effectiveness of the model in fitting a real-world dataset is demonstrated, showing better performance compared to other competing distributions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_12307 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On a new PGDUS transformed model using Inverse Weibull distribution Gauthami, P Chacko, V M Methodology Statistics Theory The Power Generalized DUS (PGDUS) Transformation is significant in reliability theory, especially for analyzing parallel systems. From the Generalized Extreme Value distribution, Inverse Weibull model particularly has wide applicability in statistics and reliability theory. In this paper we consider PGDUS transformation of Inverse Weibull distribution. The basic statistical characteristics of the new model are derived, and unknown parameters are estimated using Maximum likelihood and Maximum product of spacings methods. Simulation analysis and the reliability parameter P(T2 < T1) are explored. The effectiveness of the model in fitting a real-world dataset is demonstrated, showing better performance compared to other competing distributions. |
| title | On a new PGDUS transformed model using Inverse Weibull distribution |
| topic | Methodology Statistics Theory |
| url | https://arxiv.org/abs/2504.12307 |