The Fundamental Theorem of Markov Chains states that the long-term behavior of a Markov chain is determined by its transition probabilities and the initial state. It emphasizes that, over time, the state distribution converges to a unique stationary distribution, independent of the starting state. This theorem is crucial in understanding how Markov chains evolve and stabilize over time, revealing insights about their long-run behavior.
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