Abstract
In this paper an optimal importance sampling (IS) method is derived for a transient Markov system. Several propositions are presented. It is shown that the optimal IS method is unique, and it must converge to the standard Monte Carlo (MC) simulation method when the sample path length approaches infinity. Therefore, it is not the size of the state space of the Markov system, but the sample path length, that limits the efficiency of the IS method. Numerical results are presented to support the argument.
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