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Part I: Ergodic Rates for Markov Chains and Processes
Markov Chains with Discrete State Spaces
General Markov Chains: Ergodicity in Total Variation
Markov Processes with Continuous Time
Weak Ergodic Rates
Part II: Limit Theorems
The Law of Large Numbers and the Central Limit Theorem
Functional Limit Theorems
Coupling and Ergodic Theorems for Semi-Markov-Type Processes I
Markov Chains on Metric Spaces
Stationary Processes and Discrete Parameter Markov Processes
Markov Chains
Perturbed Semi-Markov Type Processes II
Markov Processes
Perturbed Semi-Markov Type Processes I
Continuous Parameter Markov Processes and Stochastic Differential Equations
Markov Chains: Theory and Applications
Discrete-Time Semi-Markov Random Evolutions and Their Applications
Weak Convergence of Stochastic Processes
Finite Markov Processes and Their Applications