Modern Stochastics: Theory and Applications logo


  • Help
Login Register

  1. Home
  2. Issues
  3. Volume 6, Issue 3 (2019)
  4. Taylor’s power law for the N-stars netwo ...

Modern Stochastics: Theory and Applications

Submit your article Information Become a Peer-reviewer
  • Article info
  • Full article
  • More
    Article info Full article

Taylor’s power law for the N-stars network evolution model
Volume 6, Issue 3 (2019), pp. 311–331
István Fazekas   Csaba Noszály   Noémi Uzonyi  

Authors

 
Placeholder
https://doi.org/10.15559/19-VMSTA137
Pub. online: 16 September 2019      Type: Research Article      Open accessOpen Access

Received
13 March 2019
Revised
9 August 2019
Accepted
9 August 2019
Published
16 September 2019

Abstract

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.

References

[1] 
Backhausz, A., Móri, T.F.: Weights and degrees in a random graph model based on 3-interactions. Acta Math. Hung. 143/1, 23–43 (2014) MR3215601. https://doi.org/10.1007/s10474-014-0390-8
[2] 
Barabási, A.L.: Network Science. Cambridge University Press, Cambridge (2016)
[3] 
Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286, 509–512 (1999) MR2091634. https://doi.org/10.1126/science.286.5439.509
[4] 
Bollobás, B., Riordan, O.M., Spencer, J., Tusnády, G.: The degree sequence of a scale-free random graph process. Random Struct. Algorithms 18, 279–290 (2001) MR1824277. https://doi.org/10.1002/rsa.1009
[5] 
Chung, F., Lu, L.: Complex Graphs and Networks. AMS and CBMS, Providence (2006) MR2248695. https://doi.org/10.1090/cbms/107
[6] 
Cohen, J.E., Bohk-Ewald, C., Rau, R.: Gompertz, Makeham, and Siler models explain Taylor’s law in human mortality data. Demogr. Res. 38, 773–842 (2018)
[7] 
Cohen, J.E., Xu, M., Schuster, W.S.F.: Stochastic multiplicative population growth predicts and interprets Taylor’s power law of fluctuation scaling. Proc. R. Soc. B 280, 20122955 (2013)
[8] 
Cooper, C., Frieze, A.: A general model of web graphs. Random Struct. Algorithms 22, 311–335 (2003) MR1966545. https://doi.org/10.1002/rsa.10084
[9] 
de Menezes, M.A., Barabási, A.L.: Fluctuations in network dynamics. Phys. Rev. Lett. 92, 028701 (2004)
[10] 
Durrett, R.: Random Graph Dynamics. Cambridge University Press, Cambridge (2007) MR2271734
[11] 
Eisler, Z., Bartos, I., Kertész, J.: Fluctuation scaling in complex systems: Taylor’s law and beyond. Adv. Phys. 57/1, 89142 (2008)
[12] 
Fazekas, I., Porvázsnyik, B.: Limit theorems for the weights and the degrees in an n-interactions random graph model. Open Math. 14/1, 414–424 (2016) MR3514903. https://doi.org/10.1515/math-2016-0039
[13] 
Fazekas, I., Porvázsnyik, B.: Scale-free property for degrees and weights in an n-interactions random graph model. J. Math. Sci. 214/1, 69–82 (2016) MR3476251. https://doi.org/10.1007/s10958-016-2758-5
[14] 
Fazekas, I., Noszály, C., Perecsényi, A.: The n-star network evolution model. J. Appl. Probab. 56/2, 416–440 (2019) MR3986944. https://doi.org/10.1017/jpr.2019.21
[15] 
Morris, C.N.: Natural exponential families with quadratic variance functions. Ann. Stat. 10/1, 65–80 (1982) MR0642719
[16] 
Prudnikov, A.P., Brychkov, Y.A., Marichev, O.I.: Integrals and Series. Gordon & Breach Science Publishers, New York (1986) MR0888165
[17] 
Sridharan, A., Gao, Y., Wu, K., Nastos, J.: Statistical behavior of embeddedness and communities of overlapping cliques in online social networks. In: Proceedings IEEE INFOCOM. IEEE (2011) MR2723225. https://doi.org/10.1109/TCSI.2009.2025803
[18] 
Taylor, L.R.: Aggregation, variance and the mean. Nature 189, 732–735 (1961)
[19] 
van der Hofstad, R.: Random Graphs and Complex Networks. Cambridge University Press, Cambridge (2017)

Full article PDF XML
Full article PDF XML

Copyright
© 2019 The Author(s). Published by VTeX
by logo by logo
Open access article under the CC BY license.

Keywords
Taylor’s power law random graph preferential attachment scale free gamma function

MSC2010
05C80 62E10

Funding
The research was supported by the construction EFOP-3.6.3-VEKOP-16-2017-00002; the project was supported by the European Union, co-financed by the European Social Fund.

Metrics
since March 2018
1054

Article info
views

434

Full article
views

388

PDF
downloads

175

XML
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

MSTA

MSTA

  • Online ISSN: 2351-6054
  • Print ISSN: 2351-6046
  • Copyright © 2018 VTeX

About

  • About journal
  • Indexed in
  • Editors-in-Chief

For contributors

  • Submit
  • OA Policy
  • Become a Peer-reviewer

Contact us

  • ejournals-vmsta@vtex.lt
  • Mokslininkų 2A
  • LT-08412 Vilnius
  • Lithuania
Powered by PubliMill  •  Privacy policy