Perfect simulation of processes with long memory: A “coupling into and from the past” algorithm
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Publication:4982617
DOI10.1002/rsa.20527zbMath1347.60107arXiv1106.5971OpenAlexW2963372444MaRDI QIDQ4982617
Publication date: 9 April 2015
Published in: Random Structures & Algorithms (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1106.5971
Computational methods in Markov chains (60J22) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Numerical analysis or methods applied to Markov chains (65C40)
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- On chains of infinite order
- Chains with infinite connections: Uniqueness and Markov representation
- Regenerative representation for one-dimensional Gibbs states
- Processes with long memory: Regenerative construction and perfect simulation
- Variable length Markov chains
- Testing statistical hypothesis on random trees and applications to the protein classification problem
- Context tree selection and linguistic rhythm retrieval from written texts
- Backward Coalescence Times for Perfect Simulation of Chains with Infinite Memory
- Chains with unbounded variable length memory: perfect simulation and a visible regeneration scheme
- Context tree estimation for not necessarily finite memory processes, via BIC and MDL
- Consistency of the Unlimited BIC Context Tree Estimator
- A universal data compression system
- Exact Sampling from a Continuous State Space
- The context-tree weighting method: basic properties
- Exact sampling with coupled Markov chains and applications to statistical mechanics
- How to couple from the past using a read-once source of randomness
- Simulating the Invariant Measures of Markov Chains Using Backward Coupling at Regeneration Times
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