IMPORTANCE SAMPLING VIA A SIMULACRUM

A Monte Carlo variance reduction technique known as "importance sampling" has recently been applied to many problems in data communications. This technique holds the promise of offering vast improvements to traditional Monte Carlo methods. An overview of importance sampling applied to the calculation of tail probabilities is presented, as well as examples for which some popular approaches to importance sampling fail to work. New techniques for the calculation of the resulting variances are introduced, as well as a new approach to importance sampling which offers the promise of substantial variance reduction over previous techniques. © 1990.