Taylor’s power law for the N-stars network evolution model
Open Access
- 16 September 2019
- journal article
- research article
- Published by VTeX in Modern Stochastics: Theory and Applications
- Vol. 6 (3), 311-331
- https://doi.org/10.15559/19-vmsta137
Abstract
Publisher: VTeX - Solutions for Science Publishing, Journal: Modern Stochastics - Theory and Applications, Title: Taylor’s power law for the N-stars network evolution model, Authors: István Fazekas, Csaba Noszály, Noémi Uzonyi , Taylor’s power law states that the variance function decays as a power law. It is observed for population densities of species in ecology. For random networks another power law, that is, the power law degree distribution is widely studied. In this paper the original Taylor’s power law is considered for random networks. A precise mathematical proof is presented that Taylor’s power law is asymptotically true for the N-stars network evolution model.Keywords
This publication has 15 references indexed in Scilit:
- Scale-Free Property for Degrees and Weights in an N-Interactions Random Graph Model*Journal of Mathematical Sciences, 2016
- Limit theorems for the weights and the degrees in anN-interactions random graph modelOpen Mathematics, 2016
- Weights and Degrees in a Random Graph Model Based on 3-InteractionsActa Mathematica Hungarica, 2014
- Stochastic multiplicative population growth predicts and interprets Taylor's power law of fluctuation scalingProceedings. Biological sciences, 2013
- Fluctuation scaling in complex systems: Taylor's law and beyond1Advances in Physics, 2008
- Fluctuations in Network DynamicsPhysical Review Letters, 2004
- A general model of web graphsRandom Structures & Algorithms, 2003
- The degree sequence of a scale‐free random graph processRandom Structures & Algorithms, 2001
- Natural Exponential Families with Quadratic Variance FunctionsThe Annals of Statistics, 1982
- Aggregation, Variance and the MeanNature, 1961