Steady-State Approximation for a Vector Valued Markov Chain
Management Science · 1990 · Volume 36 · Issue 8
Abstract
The problem addressed is that of a condensed steady-state solution for the Markov Chain ( X ( t ), S ( t )). The steady state marginal distribution of S ( t ) is known; we desire only the steady state marginal distribution of X ( t ). Such a case frequently arises when the supplementary random variable S ( t ) is required in the state description solely to satisfy the Markovian assumption. An iterative algorithm is presented which makes use of an approximation to the conditional distribution for S ( t ) given X ( t ).
Keywords
probability, Markov Chain, steady-state approximation
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