Random Number Generation for the New Century
Random Number Generation for the New Century
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DOI：
10.1080/00031305.2000.10474528
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发表时间：
2000-05
期刊：
影响因子：
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通讯作者：
L. Deng;D. Lin
中科院分区：
文献类型：
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作者：
L. Deng;D. Lin
使用基于计算机生成的随机数的经验研究已经成为统计方法发展中的一种常见做法，特别是当统计过程的分析研究变得棘手时。任何模拟研究的质量在很大程度上取决于随机数生成器的质量。经典的均匀随机数发生器有一些主要的缺陷，如（相对）短的周期长度和缺乏更高的维度的均匀性。介绍了两种最新的均匀伪随机数发生器（MRG和MCG）。并与经典生成器LCG进行了比较。结果表明，MRG/MCG是比流行的LCG更好的随机数发生器。介绍了MRG/MCG的特殊形式，并推荐作为新世纪的随机数发生器。还提供了用于构造这种随机数生成器的逐步过程。
Abstract Use of empirical studies based on computer-generated random numbers has become a common practice in the development of statistical methods, particularly when the analytical study of a statistical procedure becomes intractable. The quality of any simulation study depends heavily on the quality of the random number generators. Classical uniform random number generators have some major defects—such as the (relatively) short period length and the lack of higher-dimension uniformity. Two recent uniform pseudo-random number generators (MRG and MCG) are reviewed. They are compared with the classical generator LCG. It is shown that MRG/MCG are much better random number generators than the popular LCG. Special forms of MRG/MCG are introduced and recommended as the random number generators for the new century. A step-by-step procedure for constructing such random number generators is also provided.