Proxy Variable in OECD Database: Application of Parametric Quantile Regression and Median Based Unit Rayleigh Distribution
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915587212443648 |
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| author | Attia, Iman Mohamed |
| author_facet | Attia, Iman Mohamed |
| contents | This paper presents an in-depth exploration of the innovative Median-based unit Rayleigh (MBUR) distribution, previously introduced by the author. This new approach is specifically designed for conducting quantile regression analysis, enabling researchers to gain valuable insights into real-world data applications. The author effectively demonstrates the feasible advantage of the MBUR distribution, highlighting its potential to connect advanced statistical theory with meaningful results in data analysis. The author utilized OECD data in employing the parametric MBUR quantile regression using the response variables which are distributed as MBUR. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_26811 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Proxy Variable in OECD Database: Application of Parametric Quantile Regression and Median Based Unit Rayleigh Distribution Attia, Iman Mohamed Applications Methodology This paper presents an in-depth exploration of the innovative Median-based unit Rayleigh (MBUR) distribution, previously introduced by the author. This new approach is specifically designed for conducting quantile regression analysis, enabling researchers to gain valuable insights into real-world data applications. The author effectively demonstrates the feasible advantage of the MBUR distribution, highlighting its potential to connect advanced statistical theory with meaningful results in data analysis. The author utilized OECD data in employing the parametric MBUR quantile regression using the response variables which are distributed as MBUR. |
| title | Proxy Variable in OECD Database: Application of Parametric Quantile Regression and Median Based Unit Rayleigh Distribution |
| topic | Applications Methodology |
| url | https://arxiv.org/abs/2510.26811 |