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| Main Author: | |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.21663 |
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| _version_ | 1866914502374588416 |
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| author | Daures, Léo |
| author_facet | Daures, Léo |
| contents | We establish the weak large deviations principle for empirical measures of Markov chains on $\mathbb R^d$ under mild assumptions. In particular, no irreducibility is assumed and the initial measure may be arbitrary. The proof is entirely self-contained and relies on subadditivity. In the absence of irreducibility, examples show that the rate function is not convex in general. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_21663 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Large deviations for non-irreducible Markov chains on Euclidean spaces Daures, Léo Probability We establish the weak large deviations principle for empirical measures of Markov chains on $\mathbb R^d$ under mild assumptions. In particular, no irreducibility is assumed and the initial measure may be arbitrary. The proof is entirely self-contained and relies on subadditivity. In the absence of irreducibility, examples show that the rate function is not convex in general. |
| title | Large deviations for non-irreducible Markov chains on Euclidean spaces |
| topic | Probability |
| url | https://arxiv.org/abs/2604.21663 |