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In stochastic simulation, we construct mathematical models to imitate the behavior of real systems, use computers to sample behavioral histories (sample paths) of these models, and exploit those samples to improve decision making with the real system. The imitation part can be very challenging, in particular for modeling uncertainty. Fitting univariate probability distribution to data is far from...
We show via concrete illustrations how the variance can be reduced in the simulation of a telephone call center to estimate the fraction of calls answered within a given time limit. We examine the combination of a control variate and stratification with respect to a continuous input variable, and find that combining them requires care, because the optimal control variate coefficient is a function...
A portable package for uniform random number generation is proposed, based on a backbone generator with period length near 2 121 , which combines four linear congruential generators. The package provides for multiple (virtual) generators evolving in parallel. Each generator has many disjoint subsequences, and software tools are provided to reset the state of any generator to the...
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