Poisson approximation of induced subgraph counts in an inhomogeneous random intersection graph model

IF 0.6 4区 数学 Q3 MATHEMATICS Bulletin of the Korean Mathematical Society Pub Date : 2019-09-01 DOI:10.4134/BKMS.B180971
Y. Shang
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引用次数: 3

Abstract

In this paper, we consider a class of inhomogeneous random intersection graphs by assigning random weight to each vertex and two vertices are adjacent if they choose some common elements. In the inhomogeneous random intersection graph model, vertices with larger weights are more likely to acquire many elements. We show the Poisson convergence of the number of induced copies of a fixed subgraph as the number of vertices n and the number of elements m, scaling as m=⌊βnα⌋ (α,β>0), tend to infinity.
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非齐次随机交图模型中诱导子图计数的Poisson近似
本文考虑一类非齐次随机交图,通过给每个顶点分配随机权重,并且如果两个顶点选择一些公共元素,则它们是相邻的。在非均匀随机相交图模型中,权重较大的顶点更有可能获得许多元素。我们展示了固定子图的诱导拷贝数作为顶点数n和元素数m的泊松收敛性,标度为m=βnα(α,β>0),趋向于无穷大。
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来源期刊
CiteScore
0.80
自引率
20.00%
发文量
0
审稿时长
6 months
期刊介绍: This journal endeavors to publish significant research of broad interests in pure and applied mathematics. One volume is published each year, and each volume consists of six issues (January, March, May, July, September, November).
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