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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/2503.13046 |
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| _version_ | 1866909539470671872 |
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| author | Wong, Ching Moffa, Giusi Kuipers, Jack |
| author_facet | Wong, Ching Moffa, Giusi Kuipers, Jack |
| contents | The evaluation of G-Wishart normalising constants is a core component for Bayesian analyses for Gaussian graphical models, but remains a computationally intensive task in general. Based on empirical evidence, Roverato [Scandinavian Journal of Statistics, 29:391--411 (2002)] observed and conjectured that such constants can be simplified and rewritten in terms of constants with an identity scale matrix. In this note, we disprove this conjecture for general graphs by showing that the conjecture instead implies an independently-derived approximation for certain ratios of normalising constants. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_13046 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On a conjecture of Roverato regarding G-Wishart normalising constants Wong, Ching Moffa, Giusi Kuipers, Jack Statistics Theory The evaluation of G-Wishart normalising constants is a core component for Bayesian analyses for Gaussian graphical models, but remains a computationally intensive task in general. Based on empirical evidence, Roverato [Scandinavian Journal of Statistics, 29:391--411 (2002)] observed and conjectured that such constants can be simplified and rewritten in terms of constants with an identity scale matrix. In this note, we disprove this conjecture for general graphs by showing that the conjecture instead implies an independently-derived approximation for certain ratios of normalising constants. |
| title | On a conjecture of Roverato regarding G-Wishart normalising constants |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2503.13046 |