Markov Chains: Hitting Probabilities

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

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

Covers concentration inequalities and sampling methods for estimating unknown distributions, with a focus on population infection rates.

Explores the coupling of Markov chains and the proof of the ergodic theorem, emphasizing distribution convergence and chain properties.

Covers examples of absorbing Markov chains in discrete time.

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.

Covers the definitions and state probabilities of discrete-time Markov chains.

Explores birth and death chains, hitting probabilities, and expected game durations in Markov chains.

Explores Markov chains, transition matrices, distribution, and random walks.

Explores discrete-time Markov chains, emphasizing first passage time probabilities and minimal solutions.