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For a Markov chain, I define a reversible distribution to be a distribution wrt which the MC is reversible to. A stationary distribution is defined as a distribution that once reached will stay. A reversible distribution is a stationary distribution. But not vice versa.

I was wondering if a MC that has a reversible distribution can have a stationary distribution which is not a reversible distribution?

My question comes from Wikipedia:

Let $X$ be a finite set and let $K(x,y)$ be the transition probability for a reversible Markov chain on $X$. Assume this chain has stationary distribution $\pi$.

$\pi$ seems to be used as a reversible distribution in the article. I was wondering why it doesn't say $\pi$ is a distribution wrt which the MC is reversible.

Thanks and regards!

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1 Answer 1

up vote 1 down vote accepted

For an irreducible Markov chain, a stationary distribution exists if and only if all states are positive recurrent. When this condition is met, the stationary distribution is unique.

Thus, if a Markov chain (reversible or not) is irreducible and has a stationary distribution, this stationary distribution is unique.

If a Markov chain on a finite set is reversible in the sense that $\mu(x)K(x,y)=\mu(y)K(y,x)$ for every $x$ and $y$, for some measure $\mu$, then $\pi=\mu/|\mu|$ is a stationary distribution. Thus, if a Markov chain on a finite set is reversible and irreducible, it has exactly one stationary distribution, which is reversible.

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+1 Thanks! So I guess that Wikipedia article should add: the finite-state reversible MC is additionally irreducible. Can I also guess for a general reversible MC, there might be a stationary distribution which is not reversible? –  Tim Dec 13 '12 at 16:45

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