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Global Rényi index of the distance matrix

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  • Nie, Chun-Xiao
  • Song, Fu-Tie

Abstract

In previous studies, the heterogeneity of complex networks has been extensively studied. In our study, the heterogeneity of distance matrices is studied based on the Rényi index of networks. We define a new metric and name it global Rényi index (GRI), and prove several properties. In particular, the GRI value of the distance matrix corresponding to the evenly distributed point set in the Euclidean space is zero. Some model data were used to clarify the geometric meanings of GRI, and then we studied the GRI value of financial data. The results show that the GRI value in the real market changes drastically and is significantly different from the GRI value of the model-generated data. These results suggest that the proposed concept (GRI) is meaningful to the study distance matrix and provides a new perspective based on the network.

Suggested Citation

  • Nie, Chun-Xiao & Song, Fu-Tie, 2019. "Global Rényi index of the distance matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 902-915.
    • Handle: RePEc:eee:phsmap:v:514:y:2019:i:c:p:902-915
    DOI: 10.1016/j.physa.2018.09.112
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    1. Nie, Chun-Xiao, 2022. "Generalized correlation dimension and heterogeneity of network spaces," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).

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