First the entries must be nonnegative: together with the given , validity of the transition matrix requires and . Every row then sums to one.
The only incoming edge to state is , of probability . If , no other state can reach , so the chain is not irreducible. If , all edges in the directed cyclehave positive probability, since , and . Traversing this cycle connects every state to every other state. Therefore
Within the valid parameter rectangle, suppose and . The chain is then irreducible by part (i). State has a two-step return and a three-step return , both of positive probability. Its period of a state in a Markov chain therefore divides both two and three, hence equals one. Irreducibility gives the same period to every state, so the chain is aperiodic.
If and , every transition goes between the two classes and . Returns must have even length, while has length two. Thus the irreducible chain has period two.
If , the closed communicating class alternates between and . Its states have period two, using the positive two-step returns through . Consequently the chain is not aperiodic, regardless of how the transient state is classified. Combining the cases,
Here the valid parameters lie in the irreducible aperiodic range. The finite-state theorem on convergence to an invariant distribution therefore implies convergence to the unique stationary distribution, independently of the initial state.
Solve and . The equations for states giveHence and . Normalization gives , soStationarity alone would not guarantee convergence of the one-time distributions; irreducibility and aperiodicity justify that final limit.
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