Simulating Stable Stochastic Systems, II: Markov Chains
Journal of the ACM (JACM)
A decomposition approach to variance reduction
WSC '85 Proceedings of the 17th conference on Winter simulation
Combining importance sampling and temporal difference control variates to simulate Markov Chains
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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Simulators frequently wish to estimate parameters of the limiting distribution of stable stochastic processes. Several new methods for reducing the variance of such estimates will be proposed and discussed. The methods are applicable to regenerative Markov processes in both discrete and continuous time as well as to semi-Markov processes. The methods are similar to the technique of multiple control variables yet differ in the important respect that it is not necessary to calculate the means of the controls. This is because the controls are chosen in such a way that their means actually equal the parameter of interest. The methods do require a certain amount of computation to be done before the simulation begins, although their cost should be relatively minor compared with that of the simulation. Numerical results demonstrating the effectiveness of the techniques for a simple queueing model are presented.