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| Main Author: | |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.17682 |
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| _version_ | 1866909267304382464 |
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| author | Sei, Tomonari |
| author_facet | Sei, Tomonari |
| contents | A method of constructing Markov chains on finite state spaces is provided. The chain is specified by three constraints: stationarity, dependence and marginal distributions. The generalized Pythagorean theorem in information geometry plays a central role in the construction. An algorithm for obtaining the desired Markov chain is described. Integer-valued autoregressive processes are considered for illustration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_17682 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Constructing Markov chains with given dependence and marginal stationary distributions Sei, Tomonari Statistics Theory 62M05 (primary) 60J10, 62B11 (secondly) A method of constructing Markov chains on finite state spaces is provided. The chain is specified by three constraints: stationarity, dependence and marginal distributions. The generalized Pythagorean theorem in information geometry plays a central role in the construction. An algorithm for obtaining the desired Markov chain is described. Integer-valued autoregressive processes are considered for illustration. |
| title | Constructing Markov chains with given dependence and marginal stationary distributions |
| topic | Statistics Theory 62M05 (primary) 60J10, 62B11 (secondly) |
| url | https://arxiv.org/abs/2407.17682 |