Continuous-Time Markov Chains: Definitions and State Probabilities

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Explores probability inequalities, convergence types, and moment generating functions for distribution approximation.

Explores Markov chains and stationary distributions, emphasizing the importance of identifying them for improving convergence.

Explores challenges and surprises in Markov chains, analyzing convergence, state grouping, and transition probabilities.

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Explores ergodicity and stationary distribution in Markov chains, emphasizing convergence properties and unique distributions.

Introduces the key concepts of convexity and its applications in different fields.

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