标题： 基于偏差的准蒙特卡罗误差估计。III：误差分布和中心极限 显示英文标题

标题： Discrepancy-based error estimates for Quasi-Monte Carlo. III: Error distributions and central limits

摘要： 在准蒙特卡罗积分中，认为使用相同数量的积分点时，积分误差通常比经典蒙特卡罗方法更小。 通过使用适当的准随机点集集合的定义，我们推导出关于积分误差概率分布的各种结果，这些结果可以与正常随机采样的标准中心极限定理进行比较。 在许多情况下，可以获得高斯误差分布。 显示英文摘要

摘要： In Quasi-Monte Carlo integration, the integration error is believed to be generally smaller than in classical Monte Carlo with the same number of integration points. Using an appropriate definition of an ensemble of quasi-randompoint sets, we derive various results on the probability distribution of the integration error, which can be compared to the standard Central Limit theorem for normal stochastic sampling. In many cases, a Gaussian error distribution is obtained.