Mixture discrepancy for quasi-random point sets

Mixture discrepancy for quasi-random point sets
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准随机点集的混合差异

DOI:
10.1016/j.jco.2012.11.006
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发表时间:
2013-06
影响因子:
1.7
通讯作者:
Ning, Jian-Hui
Ning, Jian-Hui
中科院分区:
数学2区
文献类型:
--
作者:
Zhou, Yong-Dao;Fang, Kai-Tai;Ning, Jian-Hui

文献摘要

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对于单位超立方体上的一组点,存在各种差异,这些差异是均匀性的度量。这种差异在拟蒙特卡罗方法中起着重要的作用。每种差异都有自己的特点和弱点。本文指出了一些与文献中常用的差异有关的不合理现象,如Lp-star差异、中心l2 -差异(CD)和环绕l2 -差异(WD)。然后,提出了一种新的差异,称为混合差异(MD)。从直观的视角、子维投影的均匀性、维数的不均匀性以及核函数的几何性质等不同方面衡量均匀性,混合差异比CD和WD更为合理。此外,还给出了MD与其他设计准则如平衡模式和广义字长模式之间的关系。
There are various discrepancies that are measures of uniformity for a set of points on the unit hypercube. The discrepancies have played an important role in quasi-Monte Carlo methods. Each discrepancy has its own characteristic and some weakness. In this paper we point out some unreasonable phenomena associated with the commonly used discrepancies in the literature such as the Lp-star discrepancy, the center L2-discrepancy (CD) and the wrap-around L2-discrepancy (WD). Then, a new discrepancy, called the mixture discrepancy (MD), is proposed. As shown in this paper, the mixture discrepancy is more reasonable than CD and WD for measuring the uniformity from different aspects such as the intuitive view, the uniformity of subdimension projection, the curse of dimensionality and the geometric property of the kernel function. Moreover, the relationships between MD and other design criteria such as the balance pattern and generalized wordlength pattern are also given.
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