A perspective on variance reduction in dynamic simulation experiments

Abstract

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 variates
• common random numbers
• conditional expectations
• control variates
• generalized semi-Markov process
• importance sampling
• indirect estimators
• Latin hypercube sampling
• Monte Carlo
• poststratifying the sample
• Russian roulette
• sampling
• simulation
• splitting
• stratified sampling
• swindle
• systematic sampling
• variance reduction