BIROn - Birkbeck Institutional Research Online

A stochastic evolutionary model exhibiting power-law behaviour with an exponential cutoff

Fenner, Trevor and Levene, Mark and Loizou, George (2005) A stochastic evolutionary model exhibiting power-law behaviour with an exponential cutoff. Physica A: Statistical Mechanics and its Applications 355 (2-4), pp. 641-656. ISSN 0378-4371.

[img]
Preview
Text
Binder2.pdf

Download (330Kb) | Preview
Official URL: http://dx.doi.org/doi:10.1016/j.physa.2005.01.007

Abstract

Recently several authors have proposed stochastic evolutionary models for the growth of complex networks that give rise to power-law distributions. These models are based on the notion of preferential attachment leading to the “rich get richer” phenomenon. Despite the generality of the proposed stochastic models, there are still some unexplained phenomena, which may arise due to the limited size of networks such as protein and e-mail networks. Such networks may in fact exhibit an exponential cutoff in the power-law scaling, although this cutoff may only be observable in the tail of the distribution for extremely large networks. We propose a modification of the basic stochastic evolutionary model, so that after a node is chosen preferentially, say according to the number of its inlinks, there is a small probability that this node will be discarded. We show that as a result of this modification, by viewing the stochastic process in terms of an urn transfer model, we obtain a power-law distribution with an exponential cutoff. Unlike many other models, the current model can capture instances where the exponent of the distribution is less than or equal to two. As a proof of concept, we demonstrate the consistency of our model by analysing a yeast protein interaction network, the distribution of which is known to follow a power law with an exponential cutoff.

Item Type: Article
School or Research Centre: Birkbeck Schools and Research Centres > School of Business, Economics & Informatics > Computer Science and Information Systems
Depositing User: Sandra Plummer
Date Deposited: 12 Dec 2005
Last Modified: 17 Apr 2013 12:32
URI: http://eprints.bbk.ac.uk/id/eprint/279

Archive Staff Only (login required)

Edit/View Item Edit/View Item