
New point and interval estimators for quantiles that employ a control variate are introduced. The properties of these estimators do not depend on the usual assumption of joint normality between the random variable of interest and the control. Illustrative examples for queueing and stochastic activity network models are given. In those examples, the new estimators are superior to the standard estimator in terms of the mean squared error of the point estimator and the length of the confidence interval.
control variates, quantiles, simulation, variance reduction, maximum likelihood, unbiased tests
control variates, quantiles, simulation, variance reduction, maximum likelihood, unbiased tests
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