Suppose we have a Markov chain $X$, with transition probabilities $T_{ij} = P(X_{n+1}=i\mid X_{n}=j )$.

Let $(Y_{1}, Y_{2}, .., Y_{N})$ represent the reversed Markov chain of $X$, such that $Y_{n} = X_{N-n}$. Then, $$P(Y_{n+1}=j \mid Y_{n}=i) = T_{ij}\frac{P(Y_{n+1}=j)}{P(Y_{n}=i)}.$$ I understand that this result holds if X is homogeneous and is irrelevant whether X is irreducible.

If $X$ is an irreducible Markov chain then $T_{ij}^{(n)} \geq 0$ for each possible pair $i, j$ such that $i \neq j$, for some integer $n$.

Should one use the idea of detailed balance to show the result that an irreducible (but not necessarily homogeneous) chain must be reversible? I am unsure if the above homogeneous case helps any explanation in the context of the irreducible case.

Thank you in advance for your help and thoughts.

  • 2
    $\begingroup$ (Note that Markov was a person, so it is proper to capitalise his name when referring to a Markov chain. Same with Bayes' theorem, Fisher's test, etc.) $\endgroup$
    – Ben
    Commented Apr 12, 2020 at 1:54
  • 4
    $\begingroup$ An irreducable Markov chain is not always reversible. E.g., the Markov chain corresponding to a top-to-random shuffle on n cards (at each step taking the top card and inserting it at one of the n positions in the deck chosen uniformly at random) is irreducible, aperiodic but not reversible. $\endgroup$
    – statmerkur
    Commented Apr 12, 2020 at 9:34

1 Answer 1


Simplest example of a non-reversible irreducible Markov chain is a deterministic one with three states, that goes $1,2,3,1,2,3,1,2,3,...$

Observing that chain, you can tell if time is going forward or backward.

I think your definition of an irreducible Markov chain is flawed, also. In fact, it's vacuous; $T_{ij} \geq 0$ no matter what. You might be thinking of aperiodicity, one definition of which is that for any fixed $i,j$, $T_{ij}^{(n)}$ is always $>0$ for large $n$.


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