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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2408.00583 |
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| _version_ | 1866914896004775936 |
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| author | Boege, Tobias Drton, Mathias Hollering, Benjamin Lumpp, Sarah Misra, Pratik Schkoda, Daniela |
| author_facet | Boege, Tobias Drton, Mathias Hollering, Benjamin Lumpp, Sarah Misra, Pratik Schkoda, Daniela |
| contents | Stationary distributions of multivariate diffusion processes have recently been proposed as probabilistic models of causal systems in statistics and machine learning. Motivated by these developments, we study stationary multivariate diffusion processes with a sparsely structured drift. Our main result gives a characterization of the conditional independence relations that hold in a stationary distribution. The result draws on a graphical representation of the drift structure and pertains to conditional independence relations that hold generally as a consequence of the drift's sparsity pattern. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_00583 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Conditional Independence in Stationary Diffusions Boege, Tobias Drton, Mathias Hollering, Benjamin Lumpp, Sarah Misra, Pratik Schkoda, Daniela Statistics Theory Probability 60J60, 62H22 Stationary distributions of multivariate diffusion processes have recently been proposed as probabilistic models of causal systems in statistics and machine learning. Motivated by these developments, we study stationary multivariate diffusion processes with a sparsely structured drift. Our main result gives a characterization of the conditional independence relations that hold in a stationary distribution. The result draws on a graphical representation of the drift structure and pertains to conditional independence relations that hold generally as a consequence of the drift's sparsity pattern. |
| title | Conditional Independence in Stationary Diffusions |
| topic | Statistics Theory Probability 60J60, 62H22 |
| url | https://arxiv.org/abs/2408.00583 |