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Focus statistics for testing network centrality on uncorrelated random graphs

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  • WANG, TAI-CHI
  • PHOA, FREDERICK KIN HING

Abstract

Network centrality has been addressed for more than 30 years; however, few studies provided statistical tests for verifying this network characteristic. By applying the idea of focus test in spatial analysis, we propose a statistical method to test the centrality of a network. We consider not only the degree of node, but also give weights on other nodes with different lengths of the shortest paths, which are called “distances†in networks. According to the density of distance based on the hidden variable model and the property of the multinomial distribution, a test statistic called “focus centrality†is provided to evaluate a network centrality. Besides the theoretical construction, we verify that the proposed method is feasible and effective in the simulation studies. Further, two empirical network data are studied as demonstrations.

Suggested Citation

  • Wang, Tai-Chi & Phoa, Frederick Kin Hing, 2016. "Focus statistics for testing network centrality on uncorrelated random graphs," Network Science, Cambridge University Press, vol. 4(4), pages 460-473, December.
  • Handle: RePEc:cup:netsci:v:4:y:2016:i:04:p:460-473_00
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