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Condition numbers and scale free graphs

Author

Listed:
  • G. Acosta
  • M. Graña
  • J. P. Pinasco

Abstract

In this work we study the condition number of the least square matrix corresponding to scale free networks. We compute a theoretical lower bound of the condition number which proves that they are ill conditioned. Also, we analyze several matrices from networks generated with Linear Preferential Attachment, Edge Redirection and Attach to Edges models, showing that it is very difficult to compute the power law exponent by the least square method due to the severe lost of accuracy expected from the corresponding condition numbers. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2006

Suggested Citation

  • G. Acosta & M. Graña & J. P. Pinasco, 2006. "Condition numbers and scale free graphs," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 53(3), pages 381-385, October.
    • Handle: RePEc:spr:eurphb:v:53:y:2006:i:3:p:381-385
    DOI: 10.1140/epjb/e2006-00377-4
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    References listed on IDEAS

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    1. David A. Belsley, 1976. "Multicollinearity: Diagnosing its Presence and Assessing the Potential Damage It Causes Least Squares Estimation," NBER Working Papers 0154, National Bureau of Economic Research, Inc.
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