度序列随机实现的快速顺序创建。

Q3 Mathematics
Internet Mathematics Pub Date : 2016-01-01 Epub Date: 2016-03-24 DOI:10.1080/15427951.2016.1164768
Brian Cloteaux
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引用次数: 16

摘要

我们研究了创建非常大度序列的随机实现的问题。虽然在实践中速度很快,但由于内存限制,用于选择实现的马尔可夫链蒙特卡罗(MCMC)方法在创建大型图形时用处有限。相反,我们专注于随机图创建的顺序重要抽样(SIS)方案。SIS方案的一个难点是确保它们在合理的时间内终止。我们介绍了一种新的采样方法,在保证终止的同时达到与MCMC方法相当的速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Fast Sequential Creation of Random Realizations of Degree Sequences.

Fast Sequential Creation of Random Realizations of Degree Sequences.

Fast Sequential Creation of Random Realizations of Degree Sequences.

Fast Sequential Creation of Random Realizations of Degree Sequences.

We examine the problem of creating random realizations of very large degree sequences. Although fast in practice, the Markov chain Monte Carlo (MCMC) method for selecting a realization has limited usefulness for creating large graphs because of memory constraints. Instead, we focus on sequential importance sampling (SIS) schemes for random graph creation. A difficulty with SIS schemes is assuring that they terminate in a reasonable amount of time. We introduce a new sampling method by which we guarantee termination while achieving speed comparable to the MCMC method.

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Internet Mathematics
Internet Mathematics Mathematics-Applied Mathematics
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