Fractional Cumulative Residual Entropy in the Quantile Framework and its Applications in the Financial Data
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912214834741248 |
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| author | Sebastian, Iona Ann Sunoj, S. M. |
| author_facet | Sebastian, Iona Ann Sunoj, S. M. |
| contents | Fractional cumulative residual entropy (FCRE) is a powerful tool for the analysis of complex systems. Most of the theoretical results and applications related to the FCRE of the lifetime random variable are based on the distribution function approach. However, there are situations in which the distribution function may not be available in explicit form but has a closed-form quantile function (QF), an alternative method of representing a probability distribution. Motivated by this, in the present study we introduce a quantile-based FCRE, its dynamic version and their various properties and examine their usefulness in different applied fields. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2502_00349 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Fractional Cumulative Residual Entropy in the Quantile Framework and its Applications in the Financial Data Sebastian, Iona Ann Sunoj, S. M. Statistics Theory Fractional cumulative residual entropy (FCRE) is a powerful tool for the analysis of complex systems. Most of the theoretical results and applications related to the FCRE of the lifetime random variable are based on the distribution function approach. However, there are situations in which the distribution function may not be available in explicit form but has a closed-form quantile function (QF), an alternative method of representing a probability distribution. Motivated by this, in the present study we introduce a quantile-based FCRE, its dynamic version and their various properties and examine their usefulness in different applied fields. |
| title | Fractional Cumulative Residual Entropy in the Quantile Framework and its Applications in the Financial Data |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2502.00349 |