Gaussian Zonoids, Gaussian determinants and Gaussian random fields
Fuente:
arXiv
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| Format: | Preprint |
| Publié: |
2022
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| _version_ | 1866914962938527744 |
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| author | Mathis, Léo |
| author_facet | Mathis, Léo |
| contents | We study the Vitale zonoid (a convex body associated to a probability distribution) associated to a non--centered Gaussian vector. This defines a family of convex bodies, that contains and generalizes ellipsoids, which we call Gaussian zonoids. We show that each Gaussian zonoid can be approximated by an ellipsoid that we compute explicitely. We use this result to give new estimates for the expectation of the absolute value of the determinant of a non--centered Gaussian matrix in terms of mixed volume of ellipsoids. Finally, exploiting a recent link between random fields and zonoids uncovered by Stecconi and the author, we apply our results to the study of the zero set of non--centered Gaussian random fields. We show how these can be approximated by a suitable centered Gaussian random field and give a quantitative asymptotic in the limit where the variance goes to zero. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2203_00651 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Gaussian Zonoids, Gaussian determinants and Gaussian random fields Mathis, Léo Probability Metric Geometry We study the Vitale zonoid (a convex body associated to a probability distribution) associated to a non--centered Gaussian vector. This defines a family of convex bodies, that contains and generalizes ellipsoids, which we call Gaussian zonoids. We show that each Gaussian zonoid can be approximated by an ellipsoid that we compute explicitely. We use this result to give new estimates for the expectation of the absolute value of the determinant of a non--centered Gaussian matrix in terms of mixed volume of ellipsoids. Finally, exploiting a recent link between random fields and zonoids uncovered by Stecconi and the author, we apply our results to the study of the zero set of non--centered Gaussian random fields. We show how these can be approximated by a suitable centered Gaussian random field and give a quantitative asymptotic in the limit where the variance goes to zero. |
| title | Gaussian Zonoids, Gaussian determinants and Gaussian random fields |
| topic | Probability Metric Geometry |
| url | https://arxiv.org/abs/2203.00651 |