Discrete-Time Markov Chains: Definitions

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Page 3 of 4

Explores conditional expectation, the grouping lemma, and the law of large numbers.

Explores the Bonus Malus system for insurance premiums and Markov chain transition probabilities.

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

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

Explores Markov chains' properties, expectations, and recurrence in Poisson processes.

Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.

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

Covers the classification of states in Markov chains.

Explores Markov chain games, hitting probabilities, and expected hitting times in a target set.

Explores first passage times, strong Markov property, and state recurrence/transience in Markov chains.