加权随机块模型。

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2021-01-01 Epub Date: 2021-09-13 DOI:10.1007/s10260-021-00590-6

Tin Lok James Ng, Thomas Brendan Murphy

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引用次数: 5

摘要

我们提出了一种加权随机块模型(WSBM)，将随机块模型扩展到边被加权的重要情况。我们利用极大似然和变分方法解决了WSBM的参数估计问题，并建立了这些估计量的一致性。解决了WSBM中选择类数量的问题。将该模型应用于模拟数据和说明性数据集。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Weighted stochastic block model.

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Weighted stochastic block model.

We propose a weighted stochastic block model (WSBM) which extends the stochastic block model to the important case in which edges are weighted. We address the parameter estimation of the WSBM by use of maximum likelihood and variational approaches, and establish the consistency of these estimators. The problem of choosing the number of classes in a WSBM is addressed. The proposed model is applied to simulated data and an illustrative data set.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.