A stationary distribution is a probability distribution that remains unchanged as the process evolves over time in a Markov chain. It describes the long-term behavior of the chain, where the probabilities of being in each state stabilize and do not vary as time progresses, connecting to key concepts like state space, transition probabilities, and ergodicity.
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