A Sufficient Condition for a Unique Invariant Distribution of a Higher-Order Markov Chain

Abstract

We derive a sufficient condition for a $k$-th order homogeneous Markov chain $\mathbf{Z}$ with finite alphabet $\mathcal{Z}$ to have a unique invariant distribution on ${\mathcal{Z}}^k$. Specifically, let $\mathbf{X}$ be a first-order, stationary Markov chain with finite alphabet $\mathcal{X}$ and a single recurrent class, let $g:\mathcal{X}\to \mathcal{Z}$ be non-injective, and define the (possibly non-Markovian) process $\mathbf{Y}:=g(\mathbf{X})$ (where $g$ is applied coordinate-wise). If $\mathbf{Z}$ is the $k$-th order Markov approximation of $\mathbf{Y}$, its invariant distribution is unique. We generalize this to non-Markovian processes $\mathbf{X}$.

11 pages, 1 figure

References in corpus (1)

• Higher-Order Kullback-Leibler Aggregation of Markov Chains

Cited by in corpus (2)

• On Limiting Probability Distributions of Higher Order Markov Chains
• Can a Higher Order Markov Chain Be Treated as a First Order Markov Chain?