Computable Error Bounds for Aggregated Markov Chains

Abstract

A method is described for computing the steady-state probabdlty vector of a nearly completely decomposable Markov chain The method is closely related to one proposed by Simon and Ando and developed by Courtois However, the method described here does not require the determination of a completely decomposable stochastic approximation to the transition matrix, and hence it is applicable to nonstochasttc matrices An error analysis of the procedure which results in effectively computable error bounds is given. © 1983, ACM. All rights reserved.