On the convergence of the power series algorithm
In this paper we study the convergence properties of the power series algorithm, which gives a general method to determine (functions of) stationary distributions of Markov chains. We show that normalization plays a crucial role and that the convergence can be improved by introducing some minor changes in the algorithm. We illustrate this with several numerical examples.
power series markov chains coates graphs stationary probabilities