Quantitative Convergence Rates for Stochastically Monotone Markov Chains
Fuente:
arXiv
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910624433307648 |
|---|---|
| author | Kamihigashi, Takashi Stachurski, John |
| author_facet | Kamihigashi, Takashi Stachurski, John |
| contents | For Markov chains and Markov processes exhibiting a form of stochastic monotonicity (larger states shift up transition probabilities in terms of stochastic dominance), stability and ergodicity results can be obtained using order-theoretic mixing conditions. We complement these results by providing quantitative bounds on deviations between distributions. We also show that well-known total variation bounds can be recovered as a special case. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_19874 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Quantitative Convergence Rates for Stochastically Monotone Markov Chains Kamihigashi, Takashi Stachurski, John Probability 60G99 For Markov chains and Markov processes exhibiting a form of stochastic monotonicity (larger states shift up transition probabilities in terms of stochastic dominance), stability and ergodicity results can be obtained using order-theoretic mixing conditions. We complement these results by providing quantitative bounds on deviations between distributions. We also show that well-known total variation bounds can be recovered as a special case. |
| title | Quantitative Convergence Rates for Stochastically Monotone Markov Chains |
| topic | Probability 60G99 |
| url | https://arxiv.org/abs/2409.19874 |