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To find a stationary distribution for a Markov chain, one solves the system of linear equations given by $\pi P = \pi$, subject to the constraint that the probabilities in $\pi$ sum to 1.

Conditions: $P$ is the transition matrix of the Markov chain.; $\pi$ is a row vector of probabilities.

To find a stationary distribution for a Markov chain, one solves the system of linear equations given by $\pi P = \pi$, subject to the constraint that the probabilities in $\pi$ sum to 1.

Conditions: $P$ is the transition matrix of the Markov chain.; $\pi$ is a row vector of probabilities.