A Posteriori Error Bounds for Truncated Markov Chain Linear Systems Arising from First Transition Analysis

Many Markov chain expectations and probabilities can be computed as solutions to systems of linear equations, by applying “first transition analysis” (FTA). When the state space is infinite or very large, these linear systems become too large for exact computation. In such settings, one must truncate the FTA linear system. This paper is the first to discuss such FTA truncation issues, and to provide computable a posteriori error bounds.