Past exam of the probability course of the University of Oxford / 2014 / 3 / b

Start the Markov chain at a state $i$ and define the strictly positive first return time $T_i^{+}=\inf \{n\ge 1:X_n=i\}$. A recurrent state satisfies ${\mathbb{P}}_i(T_i^{+}<\infty )=1$; a transient state has this probability strictly below one. Equivalently a recurrent state is visited infinitely often almost surely when started there, whereas a transient state receives finitely many visits almost surely. The recurrence criterion by return probabilities gives the equivalent testStates in a communicating class share this classification. In an irreducible Markov chain all states communicate, so the chain is called a recurrent Markov chain if all its states are recurrent and a transient Markov chain if all are transient.