A perspective on variance reduction in dynamic simulation experiments

A unifying perspective on variance reduction is presented that emphasizes broadly defined variance reduction strategies rather than specific variance reduction techniques (VRTs). The perspective is based on a new taxonomy of VRTs, which is reviewed in detail. The variance reduction problem is formulated as a constrained optimization problem, and results that guarantee the effectiveness of variance reduction strategies are summarized. Keywords: antithetic variatescommon random numbersconditional expectationscontrol variatesgeneralized semi-Markov processimportance samplingindirect estimatorsLatin hypercube samplingMonte Carlopoststratifying the sampleRussian roulettesamplingsimulationsplittingstratified samplingswindlesystematic samplingvariance reduction