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Timo Vilkas
Senior lecturer
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Segregating Markov Chains
Author
Summary, in English
Dealing with finite Markov chains in discrete time, the focus often lies on convergence behavior and one tries to make different copies of the chain meet as fast as possible and then stick together. There are, however, discrete finite (reducible) Markov chains, for which two copies started in different states can be coupled to meet almost surely in finite time, yet their distributions keep a total variation distance bounded away from 0, even in the limit as time tends to infinity. We show that the supremum of total variation distance kept in this context is 12.
Publishing year
2018-09-01
Language
English
Pages
1512-1538
Publication/Series
Journal of Theoretical Probability
Volume
31
Issue
3
Document type
Journal article
Publisher
Springer
Topic
- Probability Theory and Statistics
Keywords
- Coupling inequality
- Markov chain
- Non-Markovian coupling
- Total variation distance
Status
Published
ISBN/ISSN/Other
- ISSN: 0894-9840