General Conditions for Bounded Relative Error in Simulations of Highly Reliable Markovian Systems
نویسنده
چکیده
We establish a necessary condition for any importance sampling scheme to give bounded relative error when estimating a performance measure of a highly reliable Markovian system. Also, a class of importance sampling methods is defined for which we prove a necessary and sufficient condition for bounded relative error for the performance measure estimator. This class of probability measures includes all of the currently existing failure biasing methods in the literature. Similar conditions for derivative estimators are established. SIMULATION; IMPORTANCE SAMPLING; LIKELIHOOD RATIOS; GRADIENT ESTIMATION; RELIABILITY; MARKOV CHAINS. AMS 1991 Subject Classifications: Primary: 65C05 Secondary: 60J10, 60K10
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تاریخ انتشار 1996