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Uniform point sets and the collision test

机译:均匀点集和碰撞测试

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摘要

Monte Carlo and quasi-Monte Carlo methods are popular numerical tools used in many applications. The quality of the pseudorandom sequence used in a Monte Carlo simulation is essential to the accuracy of its estimates. Likewise, the quality of the low-discrepancy sequence determines the accuracy of a quasi-Monte Carlo simulation. There is a vast literature on statistical tests that help us assess the quality of a pseudorandom sequence. However, for low-discrepancy sequences, assessing quality by estimating discrepancy is a very challenging problem, leaving us with no practical options in very high dimensions. In this paper, we will discuss how a certain interpretation of the well-known collision test for pseudorandom sequences can be used to obtain useful information about the quality of low-discrepancy sequences. Numerical examples will be used to illustrate the applications of the collision test.
机译:蒙特卡洛方法和准蒙特卡洛方法是在许多应用中使用的流行数值工具。蒙特卡洛模拟中使用的伪随机序列的质量对其估计的准确性至关重要。同样,低差异序列的质量决定了准蒙特卡罗模拟的准确性。有关统计测试的大量文献可以帮助我们评估伪随机序列的质量。但是,对于低差异序列,通过估计差异来评估质量是一个非常具有挑战性的问题,这使我们在高维度上没有实际选择。在本文中,我们将讨论如何使用众所周知的伪随机序列碰撞测试的某种解释来获得有关低差异序列质量的有用信息。数值示例将用于说明碰撞测试的应用。

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