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| The Application of Statistical Inference in Complex Networks |
| YANG Bao-ying, HU Yan-qing
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| School of Mathematics, Southwest Jiaotong University, Chengdu 611756, China |
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Abstract Complex network is the skeleton of the complex system. It composes of nodes and edges. Most of the networks have some important properties such as the power law degree distribution and the small world effect. Usually, it is not easy to justify the scale free degree distribution and estimate the parameters of the scale free distribution and to quantify both global and local network structure at the same time. In this paper, we will review the main statistics inference methods of complex networks, such as the estimation of parameters in power law distribution and exponential random graph model. Moreover, we also comment these methods from a statistical mathematical standpoint.
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Received: 06 September 2013
Published: 22 June 2026
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