First, sorry for my bad english. I am having trouble proving this exercise (it came from some notes I had back in university, I am studying for my masters next year).

Let $X$ be an aperiodic irreducible Markov chain on finite state space $S$. Let $\pi$ be stationary measure. Assume $X$ started at $\pi$. Let $a,b \in S$. Show that:

$\lim_{n \to \infty} \mathbb{P}(X_0=a, X_n=b) = \pi(a)\pi(b)$

I tried many things, including couplings, but cant figure it out. Any tips and help would be great. Thanks!

  • $\begingroup$ Have you computed $\Pr(X_0=a,X_1=b)$ yet? $\endgroup$
    – whuber
    Oct 29, 2020 at 17:36

1 Answer 1


Can't you just write \begin{align} \mathbb P(X_0 = a, X_n = b) &= P(X_0 = a) P(X_n = b \vert X_0 = a) \\ &= \pi(a) P^n_a(b), \end{align} where $P^n_a$ is the $n$-step kernel of the Markov chain started in $a$, and you assume that $X_0$ is drawn from $\pi$. By irreducibility and aperiodicity, this kernel converges to the stationary measure in the limit, so you just get $$ \lim_{n \rightarrow \infty} P^n_a(b) = \pi(b),$$ and the result follows. What am I missing?

  • $\begingroup$ Oh, ok. I am not familiar with Markov kernels (maybe I know them by another name, I studied this in portugues). What exactly is the Markov kernel? The transition matrix? $\endgroup$ Oct 29, 2020 at 11:08
  • $\begingroup$ Yes, exactly. On a discrete space that is exactly what it is. If $K$ is the transition matrix, we just have $P^n_a(b) = K^n(a,b)$. $\endgroup$ Oct 29, 2020 at 11:09
  • $\begingroup$ Great! I think I understand it now. Thank you very much! Now I am also trying to simulate this in R. Any clues how to approach it? I am a bit rusty with all this. (Also, any book recommendation or codes are very welcomed) $\endgroup$ Oct 29, 2020 at 11:12
  • $\begingroup$ You are not gonna go wrong this paper contributed to The R Journal: "Discrete Time Markov Chains with R" by Giorgio Spedicato. $\endgroup$ Oct 29, 2020 at 11:27
  • $\begingroup$ Thank you very much! You were very helpful $\endgroup$ Oct 29, 2020 at 11:33

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