Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866913998211907584 |
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| author | Karwowski, Jacek Nielsen, Frank |
| author_facet | Karwowski, Jacek Nielsen, Frank |
| contents | The extended Gaussian family is the closure of the Gaussian family obtained by completing the Gaussian family with the counterpart elements induced by degenerate covariance or degenerate precision matrices, or a mix of both degeneracies. The parameter space of the extended Gaussian family forms a symmetric positive semi-definite matrix bicone, i.e. two partial symmetric positive semi-definite matrix cones joined at their bases. In this paper, we study the Hilbert geometry of such an open bounded convex symmetric positive-definite bicone. We report the closed-form formula for the corresponding Hilbert metric distance and study exhaustively its invariance properties. We also touch upon potential applications of this geometry for dealing with extended Gaussian distributions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_14369 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family Karwowski, Jacek Nielsen, Frank Computational Geometry Machine Learning Probability The extended Gaussian family is the closure of the Gaussian family obtained by completing the Gaussian family with the counterpart elements induced by degenerate covariance or degenerate precision matrices, or a mix of both degeneracies. The parameter space of the extended Gaussian family forms a symmetric positive semi-definite matrix bicone, i.e. two partial symmetric positive semi-definite matrix cones joined at their bases. In this paper, we study the Hilbert geometry of such an open bounded convex symmetric positive-definite bicone. We report the closed-form formula for the corresponding Hilbert metric distance and study exhaustively its invariance properties. We also touch upon potential applications of this geometry for dealing with extended Gaussian distributions. |
| title | Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family |
| topic | Computational Geometry Machine Learning Probability |
| url | https://arxiv.org/abs/2508.14369 |