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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.15057 |
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| _version_ | 1866909697074790400 |
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| author | S., Smitha Andrewsa, Mary Kattumannil, Sudheesh K. |
| author_facet | S., Smitha Andrewsa, Mary Kattumannil, Sudheesh K. |
| contents | In this paper, we study the properties of the weighted entropy generating function (WEGF). We also introduce the weighted residual entropy generating function (WREGF) and establish some characterization results based on its connections with the hazard rate and the mean residual life function. Furthermore, we propose two new classes of life distributions derived from WREGF. We also study the non-parametric estimation of WREGF. A non-parametric test for the Pareto type I distribution is developed based on entropy characterization. To evaluate the performance of the test statistics, we conduct an extensive Monte Carlo simulation study. Finally, we apply the proposed method to two real-life datasets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_15057 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On Weighted Entropy Generating Function S., Smitha Andrewsa, Mary Kattumannil, Sudheesh K. Methodology In this paper, we study the properties of the weighted entropy generating function (WEGF). We also introduce the weighted residual entropy generating function (WREGF) and establish some characterization results based on its connections with the hazard rate and the mean residual life function. Furthermore, we propose two new classes of life distributions derived from WREGF. We also study the non-parametric estimation of WREGF. A non-parametric test for the Pareto type I distribution is developed based on entropy characterization. To evaluate the performance of the test statistics, we conduct an extensive Monte Carlo simulation study. Finally, we apply the proposed method to two real-life datasets. |
| title | On Weighted Entropy Generating Function |
| topic | Methodology |
| url | https://arxiv.org/abs/2507.15057 |