Control Variates for Quantile Estimation
提出使用控制变量来改进分位数的点估计和区间估计，无需假设联合正态性，在排队和随机活动网络模型中优于传统估计量。
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.