Copyright © 2012 Di Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The transition matrix, which characterizes a discrete time homogeneous
Markov chain, is a stochastic matrix. A stochastic matrix is a special nonnegative matrix with each row summing up to 1. In this paper, we focus on the computation of the
stationary distribution of a transition matrix from the viewpoint of the Perron vector
of a nonnegative matrix, based on which an algorithm for the stationary distribution
is proposed. The algorithm can also be used to compute the Perron root and the
corresponding Perron vector of any nonnegative irreducible matrix. Furthermore, a
numerical example is given to demonstrate the validity of the algorithm.