Statistical properties of a generalized threshold network model

Yusuke Ide, Norio Konno, Naoki Masuda

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The threshold network model is a type of finite random graph. In this paper, we introduce a generalized threshold network model. A pair of vertices with random weights is connected by an edge when real-valued functions of the pair of weights belong to given Borel sets. We extend several known limit theorems for the number of prescribed subgraphs and prove a uniform strong law of large numbers. We also prove two limit theorems for the local and global clustering coefficients.

Original languageEnglish
Pages (from-to)361-377
Number of pages17
JournalMethodology and Computing in Applied Probability
Volume12
Issue number3
DOIs
Publication statusPublished - 2010
Externally publishedYes

Keywords

  • Complex networks
  • Random graphs
  • Threshold network models

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)

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