Statistical Properties of a Generalized Threshold Network Model
Yusuke Ide (),
Norio Konno () and
Naoki Masuda ()
Additional contact information
Yusuke Ide: Yokohama National University
Norio Konno: Yokohama National University
Naoki Masuda: The University of Tokyo
Methodology and Computing in Applied Probability, 2010, vol. 12, issue 3, 361-377
Abstract:
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.
Keywords: Complex networks; Threshold network models; Random graphs; 05C80; 60F15 (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1007/s11009-008-9111-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:metcap:v:12:y:2010:i:3:d:10.1007_s11009-008-9111-5
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009
DOI: 10.1007/s11009-008-9111-5
Access Statistics for this article
Methodology and Computing in Applied Probability is currently edited by Joseph Glaz
More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().