English

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

Probability 2017-09-26 v2

Abstract

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

Keywords

Cite

@article{arxiv.1611.05219,
  title  = {A Sufficient Condition for a Unique Invariant Distribution of a Higher-Order Markov Chain},
  author = {Bernhard C. Geiger},
  journal= {arXiv preprint arXiv:1611.05219},
  year   = {2017}
}

Comments

11 pages, 1 figure