二部交换网络的u统计量

IF 0.6 4区数学 Q4 STATISTICS & PROBABILITY

Esaim-Probability and Statistics Pub Date : 2021-03-23 DOI:10.1051/ps/2023010

T. L. Minh

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引用次数: 1

摘要

具有可交换节点的二部网络可以用行-列可交换矩阵表示。四重组是一个大小为2 × 2的子矩阵。四联体u统计量是四联体上的函数对矩阵中所有四联体的平均值。我们证明了行-列可交换矩阵上的四重态u统计量的几个渐近结果，包括一般情况下的弱收敛结果和矩阵解离时的中心极限定理。这些结果可用于网络分析中的统计推断。我们提出了一种方法来执行参数估计，网络比较和主题计数的特定家族的行-列交换网络模型:二部期望度分布(BEDD)模型。通过仿真说明了这些应用。

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U-statistics on bipartite exchangeable networks

Bipartite networks with exchangeable nodes can be represented by row-column exchangeable matrices. A quadruplet is a submatrix of size 2 x 2. A quadruplet U-statistic is the average of a function on a quadruplet over all the quadruplets of a matrix. We prove several asymptotic results for quadruplet U-statistics on row-column exchangeable matrices, including a weak convergence result in the general case and a central limit theorem when the matrix is also dissociated. These results are applied to statistical inference in network analysis. We suggest a method to perform parameter estimation, network comparison and motifs count for a particular family of row-column exchangeable network models: the bipartite expected degree distribution (BEDD) models. These applications are illustrated by simulations.

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来源期刊

Esaim-Probability and Statistics STATISTICS & PROBABILITY-

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The journal publishes original research and survey papers in the area of Probability and Statistics. It covers theoretical and practical aspects, in any field of these domains. Of particular interest are methodological developments with application in other scientific areas, for example Biology and Genetics, Information Theory, Finance, Bioinformatics, Random structures and Random graphs, Econometrics, Physics. Long papers are very welcome. Indeed, we intend to develop the journal in the direction of applications and to open it to various fields where random mathematical modelling is important. In particular we will call (survey) papers in these areas, in order to make the random community aware of important problems of both theoretical and practical interest. We all know that many recent fascinating developments in Probability and Statistics are coming from "the outside" and we think that ESAIM: P&S should be a good entry point for such exchanges. Of course this does not mean that the journal will be only devoted to practical aspects.