Stationarity, recurrence and Markov equilibrium
A stationary distribution is a nonnegative row vector π with Σπᵢ=1 and πP=π.
Key knowledge
A stationary distribution is a nonnegative row vector π with Σπᵢ=1 and πP=π. A finite irreducible chain has a unique stationary distribution; aperiodicity additionally permits μPⁿ→π from every initial distribution. Periodic chains need not converge at individual time steps.
Conditions and scope
- Finite state space and irreducibility are explicit in this statement.
- Uniqueness of an invariant probability is different from convergence to it.
Sources · 1
References
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Evidence and review
Stationary-distribution definition, fundamental theorem and finite irreducible/aperiodic distinctions.
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Entry details
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- math-stationary-markov-laws
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- university-core.1
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- University core expansion