对具有固定度序列的双方形网络进行随机抽样的停止规则

IF 2.9 2区社会学 Q1 ANTHROPOLOGY Social Networks Pub Date : 2024-09-10 DOI:10.1016/j.socnet.2024.09.001

Zachary P. Neal

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引用次数: 0

摘要

对双元网络进行统计分析时，经常需要从与观测网络具有相同度序列的所有双元网络中随机取样。交易算法通过逐步 "交易 "部分边的位置，提供了一种生成二叉网络样本的有效方法。然而，我们很难知道需要进行多少次这样的交易才能确保样本的随机性。我提出了一种停止规则，该规则关注采样网络与观测网络之间的距离，并在该分布趋于稳定时停止执行交易。分析表明，对于超过 650 种不同的度序列，使用这种停止规则可以确保高概率的随机样本，而且它在经验应用中非常实用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A stopping rule for randomly sampling bipartite networks with fixed degree sequences

Statistical analysis of bipartite networks frequently requires randomly sampling from the set of all bipartite networks with the same degree sequence as an observed network. Trade algorithms offer an efficient way to generate samples of bipartite networks by incrementally ‘trading’ the positions of some of their edges. However, it is difficult to know how many such trades are required to ensure that the sample is random. I propose a stopping rule that focuses on the distance between sampled networks and the observed network, and stops performing trades when this distribution stabilizes. Analyses demonstrate that, for over 650 different degree sequences, using this stopping rule ensures a random sample with a high probability, and that it is practical for use in empirical applications.

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来源期刊

Social Networks Multiple-

CiteScore

5.90

自引率

12.90%

发文量

118

期刊介绍： Social Networks is an interdisciplinary and international quarterly. It provides a common forum for representatives of anthropology, sociology, history, social psychology, political science, human geography, biology, economics, communications science and other disciplines who share an interest in the study of the empirical structure of social relations and associations that may be expressed in network form. It publishes both theoretical and substantive papers. Critical reviews of major theoretical or methodological approaches using the notion of networks in the analysis of social behaviour are also included, as are reviews of recent books dealing with social networks and social structure.