Markov Chains and Mixing Times: With a Chapter on Coupling from the Past

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Introduction to finite Markov chains
Classical (and useful) Markov chains
Markov chain Monte Carlo: Metropolis and Glauber chains
Introduction to Markov chain mixing
Coupling Strong stationary times
Lower bounds on mixing times
The symmetric group and shuffling cards
Random walks on networks Hitting times
Cover times Eigenvalues
Eigenfunctions and comparison of chains
The transportation metric and path coupling
The Ising model From shuffling cards to shuffling genes
Martingales and evolving sets
The cut-off phenomenon
Lamplighter walks Continuous-time chains
Countable state-space chains
Coupling from the past Open problems
Notes on notation Appendix B: Background material
Introduction to simulation
Solutions to selected exercises
Bibliography
Index
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