Titlebook: Introduction to Rare Event Simulation; James Antonio Bucklew Book 2004 Springer Science+Business Media New York 2004 Estimator.Probability

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The Large Deviation Theory of Importance Sampling Estimators,pear to be fairly abstract but we argue that the level of generality presented here will pay dividends later on. We encourage the reader to follow the problem setup given here with some care and then compare it with the first example given below to see how this framework is actually used.

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Gaussian Systems,s numerous as are the uses of the radio spectrum. In this chapter we give a very general overview and explicitly present a theoretical framework from which a vast array of practical simulation problems can be viewed and solved.

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Universal Simulation Distributions,d depended on only one scalar parameter, the minimum rate point of the set. In this chapter we consider carrying out these techniques in the general non-Gaussian setting. Due to the special form of the multidimensional Gaussian distribution and its level sets, we could perform a closed form integrat

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The (Over-Under) Biasing Problem in Importance Sampling, situations easily computable efficient choices exist. All in all we have painted quite a rosy picture of the problem of rare event simulation. In this chapter, we indicate some of the (dangerous) problems that can face the importance sampling practitioner and how one might go about guarding against

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