On Linear Estimators for some Stable Vectors
Fuente:
arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866917203852394496 |
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| author | Chouity, Rayan Hannoun, Charbel Fahs, Jihad Abou-Faycal, Ibrahim |
| author_facet | Chouity, Rayan Hannoun, Charbel Fahs, Jihad Abou-Faycal, Ibrahim |
| contents | We consider the estimation problem for jointly stable random variables. Under two specific dependency models: a linear transformation of two independent stable variables and a sub-Gaussian symmetric $α$-stable (S$α$S) vector, we show that the conditional mean estimator is linear in both cases. Moreover, we find dispersion optimal linear estimators. Interestingly, for the sub-Gaussian (S$α$S) vector, both estimators are identical generalizing the well-known Gaussian result of the conditional mean being the best linear minimum-mean square estimator. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_09554 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | On Linear Estimators for some Stable Vectors Chouity, Rayan Hannoun, Charbel Fahs, Jihad Abou-Faycal, Ibrahim Information Theory We consider the estimation problem for jointly stable random variables. Under two specific dependency models: a linear transformation of two independent stable variables and a sub-Gaussian symmetric $α$-stable (S$α$S) vector, we show that the conditional mean estimator is linear in both cases. Moreover, we find dispersion optimal linear estimators. Interestingly, for the sub-Gaussian (S$α$S) vector, both estimators are identical generalizing the well-known Gaussian result of the conditional mean being the best linear minimum-mean square estimator. |
| title | On Linear Estimators for some Stable Vectors |
| topic | Information Theory |
| url | https://arxiv.org/abs/2601.09554 |