STOCHASTIC AND SUBSTOCHASTIC SOLUTIONS FOR INFINITE-STATE MARKOV CHAINS WITH APPLICATIONS TO MATRIX-ANALYTIC METHODS

摘要

This paper deals with censoring of infinite-state handed Markov chains. Censoring involves reducing the time spent in states outside a certain set of states to 0 without affecting the number of visits within this set. We show that, if all states are transient, there is, besides the standard censored Markov chain, it nonstandard censored Markov chain which is stochastic. Both the stochastic and the substochastic solutions are found by censoring a sequence of finite transition matrices. If all matrices in the sequence are stochastic, the stochastic Solution arises in the limit, whereas the substochastic solution arises if the matrices in the sequence are substochastic. We also show that, if the Markov chain is recurrent, the Only Solution is the stochastic solution. Censoring is particularly fruitful when applied to quasi-birth-and-death (QBD) processes. It turns out that key matrices in such processes are not unique, a fact that has been observed by several queues. authors. We note that the stochastic solution is important for the analysis of finite queues.